diff --git a/app/br/br.cpp b/app/br/br.cpp
index 8615274..475e81f 100644
--- a/app/br/br.cpp
+++ b/app/br/br.cpp
@@ -129,8 +129,8 @@ public:
                 check(parc == 3, "Incorrect parameter count for 'convert'.");
                 br_convert(parv[0], parv[1], parv[2]);
             } else if (!strcmp(fun, "evalClassification")) {
-                check(parc == 2, "Incorrect parameter count for 'evalClassification'.");
-                br_eval_classification(parv[0], parv[1]);
+                check(parc >= 2 && parc <= 4, "Incorrect parameter count for 'evalClassification'.");
+                br_eval_classification(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc >= 4 ? parv[3] : "");
             } else if (!strcmp(fun, "evalClustering")) {
                 check(parc == 2, "Incorrect parameter count for 'evalClustering'.");
                 br_eval_clustering(parv[0], parv[1]);
@@ -138,8 +138,8 @@ public:
                 check((parc >= 2) && (parc <= 3), "Incorrect parameter count for 'evalDetection'.");
                 br_eval_detection(parv[0], parv[1], parc == 3 ? parv[2] : "");
             } else if (!strcmp(fun, "evalRegression")) {
-                check(parc == 2, "Incorrect parameter count for 'evalRegression'.");
-                br_eval_regression(parv[0], parv[1]);
+                check(parc >= 2 && parc <= 4, "Incorrect parameter count for 'evalRegression'.");
+                br_eval_regression(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc >= 4 ? parv[3] : "");
             } else if (!strcmp(fun, "plotDetection")) {
                 check(parc >= 2, "Incorrect parameter count for 'plotDetection'.");
                 br_plot_detection(parc-1, parv, parv[parc-1], true);
@@ -215,10 +215,10 @@ private:
                "-combineMasks <mask> ... <mask> {mask} (And|Or)\n"
                "-cat <gallery> ... <gallery> {gallery}\n"
                "-convert (Format|Gallery|Output) <input_file> {output_file}\n"
-               "-evalClassification <predicted_gallery> <truth_gallery>\n"
+               "-evalClassification <predicted_gallery> <truth_gallery> <predicted property name> <ground truth proprty name>\n"
                "-evalClustering <clusters> <gallery>\n"
                "-evalDetection <predicted_gallery> <truth_gallery> [{csv}]\n"
-               "-evalRegression <predicted_gallery> <truth_gallery>\n"
+               "-evalRegression <predicted_gallery> <truth_gallery> <predicted property name> <ground truth property name>\n"
                "-plotDetection <file> ... <file> {destination}\n"
                "-plotMetadata <file> ... <file> <columns>\n"
                "-getHeader <matrix>\n"
diff --git a/app/examples/age_estimation.cpp b/app/examples/age_estimation.cpp
index c2a90e5..2958b71 100644
--- a/app/examples/age_estimation.cpp
+++ b/app/examples/age_estimation.cpp
@@ -29,7 +29,7 @@
 
 static void printTemplate(const br::Template &t)
 {
-    printf("%s age: %d\n", qPrintable(t.file.fileName()), int(t.file.get<float>("Subject")));
+    printf("%s age: %d\n", qPrintable(t.file.fileName()), int(t.file.get<float>("Age")));
 }
 
 int main(int argc, char *argv[])
diff --git a/app/examples/gender_estimation.cpp b/app/examples/gender_estimation.cpp
index dd4ebd2..d2a824d 100644
--- a/app/examples/gender_estimation.cpp
+++ b/app/examples/gender_estimation.cpp
@@ -29,7 +29,7 @@
 
 static void printTemplate(const br::Template &t)
 {
-    printf("%s gender: %s\n", qPrintable(t.file.fileName()), qPrintable(t.file.get<QString>("Subject")));
+    printf("%s gender: %s\n", qPrintable(t.file.fileName()), qPrintable(t.file.get<QString>("Gender")));
 }
 
 int main(int argc, char *argv[])
diff --git a/openbr/core/bee.cpp b/openbr/core/bee.cpp
index c6cb254..9639657 100644
--- a/openbr/core/bee.cpp
+++ b/openbr/core/bee.cpp
@@ -99,10 +99,10 @@ void BEE::writeSigset(const QString &sigset, const br::FileList &files, bool ign
         QStringList metadata;
         if (!ignoreMetadata)
             foreach (const QString &key, file.localKeys()) {
-                if ((key == "Index") || (key == "Subject")) continue;
+                if ((key == "Index") || (key == "Label")) continue;
                 metadata.append(key+"=\""+QtUtils::toString(file.value(key))+"\"");
             }
-        lines.append("\t<biometric-signature name=\"" + file.get<QString>("Subject",file.fileName()) +"\">");
+        lines.append("\t<biometric-signature name=\"" + file.get<QString>("Label",file.fileName()) +"\">");
         lines.append("\t\t<presentation file-name=\"" + file.name + "\" " + metadata.join(" ") + "/>");
         lines.append("\t</biometric-signature>");
     }
@@ -266,10 +266,11 @@ void BEE::makeMask(const QString &targetInput, const QString &queryInput, const 
 
 cv::Mat BEE::makeMask(const br::FileList &targets, const br::FileList &queries, int partition)
 {
-    // Would like to use indexProperty for this, but didn't make a version of that for Filelist yet
-    // -cao
-    QList<QString> targetLabels = File::get<QString>(targets, "Subject", "-1");
-    QList<QString> queryLabels = File::get<QString>(queries, "Subject", "-1");
+    // Direct use of "Label" isn't general, also would prefer to use indexProperty, rather than
+    // doing string comparisons (but that isn't implemented yet for FileList) -cao
+    QList<QString> targetLabels = File::get<QString>(targets, "Label", "-1");
+    QList<QString> queryLabels = File::get<QString>(queries, "Label", "-1");
+
     QList<int> targetPartitions = targets.crossValidationPartitions();
     QList<int> queryPartitions = queries.crossValidationPartitions();
 
diff --git a/openbr/core/cluster.cpp b/openbr/core/cluster.cpp
index 6a6b954..8c880d9 100644
--- a/openbr/core/cluster.cpp
+++ b/openbr/core/cluster.cpp
@@ -279,8 +279,8 @@ void br::EvalClustering(const QString &csv, const QString &input)
     qDebug("Evaluating %s against %s", qPrintable(csv), qPrintable(input));
 
     // We assume clustering algorithms store assigned cluster labels as integers (since the clusters are
-    // not named).
-    QList<int> labels = File::get<int>(TemplateList::fromGallery(input), "Subject");
+    // not named). Direct use of ClusterID is not general -cao
+    QList<int> labels = File::get<int>(TemplateList::fromGallery(input), "ClusterID");
 
     QHash<int, int> labelToIndex;
     int nClusters = 0;
diff --git a/openbr/core/common.cpp b/openbr/core/common.cpp
index 17584ec..55cbd3e 100644
--- a/openbr/core/common.cpp
+++ b/openbr/core/common.cpp
@@ -15,11 +15,15 @@
  * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
 
 #include "common.h"
+#include <QMutex>
 
 using namespace std;
 
 /**** GLOBAL ****/
 void Common::seedRNG() {
+    static QMutex seedControl;
+    QMutexLocker lock(&seedControl);
+
     static bool seeded = false;
     if (!seeded) {
         srand(0); // We seed with 0 instead of time(NULL) to have reproducible randomness
@@ -29,8 +33,6 @@ void Common::seedRNG() {
 
 QList<int> Common::RandSample(int n, int max, int min, bool unique)
 {
-    seedRNG();
-
     QList<int> samples; samples.reserve(n);
     int range = max-min;
     if (range <= 0) qFatal("Non-positive range.");
@@ -50,8 +52,6 @@ QList<int> Common::RandSample(int n, int max, int min, bool unique)
 
 QList<int> Common::RandSample(int n, const QSet<int> &values, bool unique)
 {
-    seedRNG();
-
     QList<int> valueList = values.toList();
     if (unique && (values.size() <= n)) return valueList;
 
diff --git a/openbr/core/eval.cpp b/openbr/core/eval.cpp
index 9e813d8..a87807e 100644
--- a/openbr/core/eval.cpp
+++ b/openbr/core/eval.cpp
@@ -255,9 +255,20 @@ struct Counter
     }
 };
 
-void EvalClassification(const QString &predictedInput, const QString &truthInput)
+void EvalClassification(const QString &predictedInput, const QString &truthInput, QString predictedProperty, QString truthProperty)
 {
     qDebug("Evaluating classification of %s against %s", qPrintable(predictedInput), qPrintable(truthInput));
+
+    if (predictedProperty.isEmpty())
+        predictedProperty = "Label";
+    // If predictedProperty is specified, but truthProperty isn't, copy over the value from
+    // predicted property
+    else if (truthProperty.isEmpty())
+        truthProperty = predictedProperty;
+
+    if (truthProperty.isEmpty())
+        truthProperty = "Label";
+
     TemplateList predicted(TemplateList::fromGallery(predictedInput));
     TemplateList truth(TemplateList::fromGallery(truthInput));
     if (predicted.size() != truth.size()) qFatal("Input size mismatch.");
@@ -267,9 +278,8 @@ void EvalClassification(const QString &predictedInput, const QString &truthInput
         if (predicted[i].file.name != truth[i].file.name)
             qFatal("Input order mismatch.");
 
-        // Typically these lists will be of length one, but this generalization allows measuring multi-class labeling accuracy.
-        QString predictedSubject = predicted[i].file.get<QString>("Subject");
-        QString trueSubject = truth[i].file.get<QString>("Subject");
+        QString predictedSubject = predicted[i].file.get<QString>(predictedProperty);
+        QString trueSubject = truth[i].file.get<QString>(truthProperty);
 
         QStringList predictedSubjects(predictedSubject);
         QStringList trueSubjects(trueSubject);
@@ -466,21 +476,37 @@ float EvalDetection(const QString &predictedInput, const QString &truthInput, co
     return averageOverlap;
 }
 
-void EvalRegression(const QString &predictedInput, const QString &truthInput)
+void EvalRegression(const QString &predictedInput, const QString &truthInput, QString predictedProperty, QString truthProperty)
 {
     qDebug("Evaluating regression of %s against %s", qPrintable(predictedInput), qPrintable(truthInput));
+
+    if (predictedProperty.isEmpty())
+        predictedProperty = "Regressor";
+    // If predictedProperty is specified, but truthProperty isn't, copy the value over
+    // rather than using the default for truthProperty
+    else if (truthProperty.isEmpty())
+        truthProperty = predictedProperty;
+
+    if (truthProperty.isEmpty())
+        predictedProperty = "Regressand";
+
     const TemplateList predicted(TemplateList::fromGallery(predictedInput));
     const TemplateList truth(TemplateList::fromGallery(truthInput));
     if (predicted.size() != truth.size()) qFatal("Input size mismatch.");
 
     float rmsError = 0;
+    float maeError = 0;
     QStringList truthValues, predictedValues;
     for (int i=0; i<predicted.size(); i++) {
         if (predicted[i].file.name != truth[i].file.name)
             qFatal("Input order mismatch.");
-        rmsError += pow(predicted[i].file.get<float>("Subject")-truth[i].file.get<float>("Subject"), 2.f);
-        truthValues.append(QString::number(truth[i].file.get<float>("Subject")));
-        predictedValues.append(QString::number(predicted[i].file.get<float>("Subject")));
+
+        float difference = predicted[i].file.get<float>(predictedProperty) - truth[i].file.get<float>(truthProperty);
+
+        rmsError += pow(difference, 2.f);
+        maeError += fabsf(difference);
+        truthValues.append(QString::number(truth[i].file.get<float>(truthProperty)));
+        predictedValues.append(QString::number(predicted[i].file.get<float>(predictedProperty)));
     }
 
     QStringList rSource;
@@ -500,6 +526,7 @@ void EvalRegression(const QString &predictedInput, const QString &truthInput)
     if (success) QtUtils::showFile("EvalRegression.pdf");
 
     qDebug("RMS Error = %f", sqrt(rmsError/predicted.size()));
+    qDebug("MAE = %f", maeError/predicted.size());
 }
 
 } // namespace br
diff --git a/openbr/core/eval.h b/openbr/core/eval.h
index d90d1a5..b4f199d 100644
--- a/openbr/core/eval.h
+++ b/openbr/core/eval.h
@@ -26,9 +26,9 @@ namespace br
     float Evaluate(const QString &simmat, const QString &mask = "", const QString &csv = ""); // Returns TAR @ FAR = 0.001
     float Evaluate(const cv::Mat &scores, const FileList &target, const FileList &query, const QString &csv = "", int parition = 0);
     float Evaluate(const cv::Mat &scores, const cv::Mat &masks, const QString &csv = "");
-    void EvalClassification(const QString &predictedInput, const QString &truthInput);
+    void EvalClassification(const QString &predictedInput, const QString &truthInput, QString predictedProperty="", QString truthProperty="");
     float EvalDetection(const QString &predictedInput, const QString &truthInput, const QString &csv = ""); // Return average overlap
-    void EvalRegression(const QString &predictedInput, const QString &truthInput);
+    void EvalRegression(const QString &predictedInput, const QString &truthInput, QString predictedProperty="", QString truthProperty="");
 }
 
 #endif // __EVAL_H
diff --git a/openbr/frvt2012.cpp b/openbr/frvt2012.cpp
index ac47ac8..b0c2d29 100644
--- a/openbr/frvt2012.cpp
+++ b/openbr/frvt2012.cpp
@@ -132,7 +132,7 @@ int32_t SdkEstimator::estimate_age(const ONEFACE &input_face, int32_t &age)
     TemplateList templates;
     templates.append(templateFromONEFACE(input_face));
     templates >> *frvt2012_age_transform.data();
-    age = templates.first().file.get<float>("Subject");
+    age = templates.first().file.get<float>("Age");
     return templates.first().file.failed() ? 4 : 0;
 }
 
@@ -141,6 +141,6 @@ int32_t SdkEstimator::estimate_gender(const ONEFACE &input_face, int8_t &gender,
     TemplateList templates;
     templates.append(templateFromONEFACE(input_face));
     templates >> *frvt2012_gender_transform.data();
-    mf = gender = templates.first().file.get<QString>("Subject") == "Male" ? 0 : 1;
+    mf = gender = templates.first().file.get<QString>("Gender") == "Male" ? 0 : 1;
     return templates.first().file.failed() ? 4 : 0;
 }
diff --git a/openbr/gui/classifier.cpp b/openbr/gui/classifier.cpp
index 2df9f5e..71a3102 100644
--- a/openbr/gui/classifier.cpp
+++ b/openbr/gui/classifier.cpp
@@ -39,19 +39,23 @@ void Classifier::_classify(File file)
 {
     QString key, value;
     foreach (const File &f, Enroll(file.flat(), File("[algorithm=" + algorithm + "]"))) {
-        if (!f.contains("Label"))
-            continue;
 
         if (algorithm == "GenderClassification") {
             key = "Gender";
-            value = (f.get<QString>("Subject"));
         } else if (algorithm == "AgeRegression") {
             key = "Age";
-            value = QString::number(int(f.get<float>("Subject")+0.5)) + " Years";
         } else {
             key = algorithm;
-            value = f.get<QString>("Subject");
         }
+
+        if (!f.contains(key))
+            continue;
+
+        if (algorithm == "AgeRegression")
+            value = QString::number(int(f.get<float>(key)+0.5)) + " Years";
+        else
+            value = f.get<QString>(key);
+
         break;
     }
 
diff --git a/openbr/openbr.cpp b/openbr/openbr.cpp
index c269366..09ca043 100644
--- a/openbr/openbr.cpp
+++ b/openbr/openbr.cpp
@@ -72,9 +72,9 @@ float br_eval(const char *simmat, const char *mask, const char *csv)
     return Evaluate(simmat, mask, csv);
 }
 
-void br_eval_classification(const char *predicted_gallery, const char *truth_gallery)
+void br_eval_classification(const char *predicted_gallery, const char *truth_gallery, const char *predicted_property, const char * truth_property)
 {
-    EvalClassification(predicted_gallery, truth_gallery);
+    EvalClassification(predicted_gallery, truth_gallery, predicted_property, truth_property);
 }
 
 void br_eval_clustering(const char *csv, const char *gallery)
@@ -87,9 +87,9 @@ float br_eval_detection(const char *predicted_gallery, const char *truth_gallery
     return EvalDetection(predicted_gallery, truth_gallery, csv);
 }
 
-void br_eval_regression(const char *predicted_gallery, const char *truth_gallery)
+void br_eval_regression(const char *predicted_gallery, const char *truth_gallery, const char * predicted_property, const char * truth_property)
 {
-    EvalRegression(predicted_gallery, truth_gallery);
+    EvalRegression(predicted_gallery, truth_gallery, predicted_property, truth_property);
 }
 
 void br_finalize()
diff --git a/openbr/openbr.h b/openbr/openbr.h
index 6d96a28..6a26a77 100644
--- a/openbr/openbr.h
+++ b/openbr/openbr.h
@@ -149,7 +149,7 @@ BR_EXPORT float br_eval(const char *simmat, const char *mask, const char *csv = 
  * \param predicted_gallery The predicted br::Gallery.
  * \param truth_gallery The ground truth br::Gallery.
  */
-BR_EXPORT void br_eval_classification(const char *predicted_gallery, const char *truth_gallery);
+BR_EXPORT void br_eval_classification(const char *predicted_gallery, const char *truth_gallery, const char * predicted_property="", const char * truth_property="");
 
 /*!
  * \brief Evaluates and prints clustering accuracy to the terminal.
@@ -173,7 +173,7 @@ BR_EXPORT float br_eval_detection(const char *predicted_gallery, const char *tru
  * \param predicted_gallery The predicted br::Gallery.
  * \param truth_gallery The ground truth br::Gallery.
  */
-BR_EXPORT void br_eval_regression(const char *predicted_gallery, const char *truth_gallery);
+BR_EXPORT void br_eval_regression(const char *predicted_gallery, const char *truth_gallery, const char * predicted_property="", const char * truth_property="");
 
 /*!
  * \brief Wraps br::Context::finalize()
diff --git a/openbr/openbr_plugin.cpp b/openbr/openbr_plugin.cpp
index 1becbbf..38aeb80 100644
--- a/openbr/openbr_plugin.cpp
+++ b/openbr/openbr_plugin.cpp
@@ -412,7 +412,8 @@ TemplateList TemplateList::fromGallery(const br::File &gallery)
                     // of target images to every partition
                     newTemplates[i].file.set("Partition", -1);
                 } else {
-                    const QByteArray md5 = QCryptographicHash::hash(newTemplates[i].file.get<QString>("Subject").toLatin1(), QCryptographicHash::Md5);
+                    // Direct use of "Label" is not general -cao
+                    const QByteArray md5 = QCryptographicHash::hash(newTemplates[i].file.get<QString>("Label").toLatin1(), QCryptographicHash::Md5);
                     // Select the right 8 hex characters so that it can be represented as a 64 bit integer without overflow
                     newTemplates[i].file.set("Partition", md5.toHex().right(8).toULongLong(0, 16) % crossValidate);
                 }
@@ -890,6 +891,8 @@ void br::Context::initialize(int &argc, char *argv[], QString sdkPath, bool use_
 
     qInstallMessageHandler(messageHandler);
 
+    Common::seedRNG();
+
     // Search for SDK
     if (sdkPath.isEmpty()) {
         QStringList checkPaths; checkPaths << QDir::currentPath() << QCoreApplication::applicationDirPath();
@@ -1082,9 +1085,6 @@ Transform::Transform(bool _independent, bool _trainable)
 {
     independent = _independent;
     trainable = _trainable;
-    classes = std::numeric_limits<int>::max();
-    instances = std::numeric_limits<int>::max();
-    fraction = 1;
 }
 
 Transform *Transform::make(QString str, QObject *parent)
@@ -1140,9 +1140,6 @@ Transform *Transform::make(QString str, QObject *parent)
 Transform *Transform::clone() const
 {
     Transform *clone = Factory<Transform>::make(file.flat());
-    clone->classes = classes;
-    clone->instances = instances;
-    clone->fraction = fraction;
     return clone;
 }
 
diff --git a/openbr/openbr_plugin.h b/openbr/openbr_plugin.h
index a5171b2..0f0d800 100644
--- a/openbr/openbr_plugin.h
+++ b/openbr/openbr_plugin.h
@@ -130,13 +130,6 @@ void reset_##NAME() { NAME = DEFAULT; }
  * -# If the value is convertable to a floating point number then it is represented with \c float.
  * -# Otherwise, it is represented with \c QString.
  *
- * The metadata keys \c Subject and \c Label have special significance in the system.
- * \c Subject is a string specifying a unique identifier used to determine ground truth match/non-match.
- * \c Label is a floating point value used for supervised learning.
- * When the system needs labels for training, but only subjects are provided in the file metadata, the rule for generating labels is as follows.
- * If the subject value can be converted to a float then do so and consider that the label.
- * Otherwise, generate a unique integer ID for the string starting from zero and incrementing by one everytime another ID is needed.
- *
  * Metadata keys fall into one of two categories:
  * - \c camelCaseKeys are inputs that specify how to process the file.
  * - \c Capitalized_Underscored_Keys are outputs computed from processing the file.
@@ -147,8 +140,6 @@ void reset_##NAME() { NAME = DEFAULT; }
  * ---             | ----           | -----------
  * separator       | QString        | Seperate #name into multiple files
  * Index           | int            | Index of a template in a template list
- * Subject         | QString        | Class name
- * Label           | float          | Class value
  * Confidence      | float          | Classification/Regression quality
  * FTE             | bool           | Failure to enroll
  * FTO             | bool           | Failure to open
@@ -157,13 +148,15 @@ void reset_##NAME() { NAME = DEFAULT; }
  * *_Width         | float          | Size
  * *_Height        | float          | Size
  * *_Radius        | float          | Size
+ * Label           | QString        | Class label
  * Theta           | float          | Pose
  * Roll            | float          | Pose
  * Pitch           | float          | Pose
  * Yaw             | float          | Pose
  * Points          | QList<QPointF> | List of unnamed points
  * Rects           | QList<Rect>    | List of unnamed rects
- * Age             | QString        | Age used for demographic filtering
+ * Age             | float          | Age used for demographic filtering
+ * Gender          | QString        | Subject gender
  * _*              | *              | Reserved for internal use
  */
 struct BR_EXPORT File
@@ -172,7 +165,7 @@ struct BR_EXPORT File
 
     File() {}
     File(const QString &file) { init(file); } /*!< \brief Construct a file from a string. */
-    File(const QString &file, const QVariant &subject) { init(file); set("Subject", subject); } /*!< \brief Construct a file from a string and assign a label. */
+    File(const QString &file, const QVariant &label) { init(file); set("Label", label); } /*!< \brief Construct a file from a string and assign a label. */
     File(const char *file) { init(file); } /*!< \brief Construct a file from a c-style string. */
     inline operator QString() const { return name; } /*!< \brief Returns #name. */
     QString flat() const; /*!< \brief A stringified version of the file with metadata. */
@@ -1058,12 +1051,6 @@ class BR_EXPORT Transform : public Object
     Q_OBJECT
 
 public:
-    Q_PROPERTY(int classes READ get_classes WRITE set_classes RESET reset_classes STORED false)
-    Q_PROPERTY(int instances READ get_instances WRITE set_instances RESET reset_instances STORED false)
-    Q_PROPERTY(float fraction READ get_fraction WRITE set_fraction RESET reset_fraction STORED false)
-    BR_PROPERTY(int, classes, std::numeric_limits<int>::max())
-    BR_PROPERTY(int, instances, std::numeric_limits<int>::max())
-    BR_PROPERTY(float, fraction, 1)
     bool independent, trainable;
 
     virtual ~Transform() {}
diff --git a/openbr/plugins/algorithms.cpp b/openbr/plugins/algorithms.cpp
index 809a112..48154af 100644
--- a/openbr/plugins/algorithms.cpp
+++ b/openbr/plugins/algorithms.cpp
@@ -48,7 +48,7 @@ class AlgorithmsInitializer : public Initializer
         // Video
         Globals->abbreviations.insert("DisplayVideo", "Stream([FPSLimit(30)+Show(false,[FrameNumber])+Discard])");
         Globals->abbreviations.insert("PerFrameDetection", "Stream([SaveMat(original)+Cvt(Gray)+Cascade(FrontalFace)+ASEFEyes+RestoreMat(original)+Draw(inPlace=true),Show(false,[FrameNumber])+Discard])");
-        Globals->abbreviations.insert("AgeGenderDemo", "Stream([SaveMat(original)+Cvt(Gray)+Cascade(FrontalFace)+Expand+<FaceClassificationRegistration>+<FaceClassificationExtraction>+(<AgeRegressor>+Rename(Subject,Age)+Discard)/(<GenderClassifier>+Rename(Subject,Gender)+Discard)+RestoreMat(original)+Draw(inPlace=true)+DrawPropertiesPoint([Age,Gender],Affine_0,inPlace=true)+SaveMat(original)+Discard+Contract,RestoreMat(original)+FPSCalc+Show(false,[AvgFPS,Age,Gender])+Discard])");
+        Globals->abbreviations.insert("AgeGenderDemo", "Stream([SaveMat(original)+Cvt(Gray)+Cascade(FrontalFace)+Expand+<FaceClassificationRegistration>+<FaceClassificationExtraction>+<AgeRegressor>/<GenderClassifier>+Discard+RestoreMat(original)+Draw(inPlace=true)+DrawPropertiesPoint([Age,Gender],Affine_0,inPlace=true)+SaveMat(original)+Discard+Contract,RestoreMat(original)+FPSCalc+Show(false,[AvgFPS,Age,Gender])+Discard])");
         Globals->abbreviations.insert("BoVW", "Flatten+CatRows+KMeans(500)+Hist(500)");
         Globals->abbreviations.insert("HOF", "Stream([KeyPointDetector(SIFT),AggregateFrames(2)+OpticalFlow,ROI,HoGDescriptor])+BoVW");
         Globals->abbreviations.insert("HoG", "Stream([KeyPointDetector(SIFT),ROI,HoGDescriptor])+BoVW");
@@ -78,14 +78,14 @@ class AlgorithmsInitializer : public Initializer
         Globals->abbreviations.insert("FaceDetection", "(Open+Cvt(Gray)+Cascade(FrontalFace))");
         Globals->abbreviations.insert("DenseLBP", "(Blur(1.1)+Gamma(0.2)+DoG(1,2)+ContrastEq(0.1,10)+LBP(1,2)+RectRegions(8,8,6,6)+Hist(59))");
         Globals->abbreviations.insert("DenseSIFT", "(Grid(10,10)+SIFTDescriptor(12)+ByRow)");
-        Globals->abbreviations.insert("FaceRecognitionRegistration", "(ASEFEyes+Affine(88,88,0.25,0.35)+FTE(DFFS,instances=1))");
-        Globals->abbreviations.insert("FaceRecognitionExtraction", "(Mask+DenseSIFT/DenseLBP+PCA(0.95,instances=1)+Normalize(L2)+Cat)");
-        Globals->abbreviations.insert("FaceRecognitionEmbedding", "(Dup(12)+RndSubspace(0.05,1)+LDA(0.98,instances=-2)+Cat+PCA(768,instances=1))");
+        Globals->abbreviations.insert("FaceRecognitionRegistration", "(ASEFEyes+Affine(88,88,0.25,0.35)+DownsampleTraining(FTE(DFFS),instances=1))");
+        Globals->abbreviations.insert("FaceRecognitionExtraction", "(Mask+DenseSIFT/DenseLBP+DownsampleTraining(PCA(0.95),instances=1)+Normalize(L2)+Cat)");
+        Globals->abbreviations.insert("FaceRecognitionEmbedding", "(Dup(12)+RndSubspace(0.05,1)+DownsampleTraining(LDA(0.98),instances=-2)+Cat+DownsampleTraining(PCA(768),instances=1))");
         Globals->abbreviations.insert("FaceRecognitionQuantization", "(Normalize(L1)+Quantize)");
         Globals->abbreviations.insert("FaceClassificationRegistration", "(ASEFEyes+Affine(56,72,0.33,0.45)+FTE(DFFS))");
-        Globals->abbreviations.insert("FaceClassificationExtraction", "((Grid(7,7)+SIFTDescriptor(8)+ByRow)/DenseLBP+PCA(0.95,instances=-1)+Cat)");
-        Globals->abbreviations.insert("AgeRegressor", "Center(Range,instances=-1)+SVM(RBF,EPS_SVR,instances=100)");
-        Globals->abbreviations.insert("GenderClassifier", "Center(Range,instances=-1)+SVM(RBF,C_SVC,instances=4000)");
+        Globals->abbreviations.insert("FaceClassificationExtraction", "((Grid(7,7)+SIFTDescriptor(8)+ByRow)/DenseLBP+DownsampleTraining(PCA(0.95),instances=-1, inputVariable=Gender)+Cat)");
+        Globals->abbreviations.insert("AgeRegressor", "DownsampleTraining(Center(Range),instances=-1, inputVariable=Age)+DownsampleTraining(SVM(RBF,EPS_SVR,inputVariable=Age),instances=100, inputVariable=Age)");
+        Globals->abbreviations.insert("GenderClassifier", "DownsampleTraining(Center(Range),instances=-1, inputVariable=Gender)+DownsampleTraining(SVM(RBF,C_SVC,inputVariable=Gender),instances=4000, inputVariable=Gender)");
         Globals->abbreviations.insert("UCharL1", "Unit(ByteL1)");
     }
 };
diff --git a/openbr/plugins/cluster.cpp b/openbr/plugins/cluster.cpp
index e6ff87c..3a9b577 100644
--- a/openbr/plugins/cluster.cpp
+++ b/openbr/plugins/cluster.cpp
@@ -89,10 +89,14 @@ class KNNTransform : public Transform
     Q_PROPERTY(br::Distance *distance READ get_distance WRITE set_distance RESET reset_distance STORED false)
     Q_PROPERTY(bool weighted READ get_weighted WRITE set_weighted RESET reset_weighted STORED false)
     Q_PROPERTY(int numSubjects READ get_numSubjects WRITE set_numSubjects RESET reset_numSubjects STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
+    Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false)
     BR_PROPERTY(int, k, 1)
     BR_PROPERTY(br::Distance*, distance, NULL)
     BR_PROPERTY(bool, weighted, false)
     BR_PROPERTY(int, numSubjects, 1)
+    BR_PROPERTY(QString, inputVariable, "Label")
+    BR_PROPERTY(QString, outputVariable, "KNN")
 
     TemplateList gallery;
 
@@ -111,17 +115,17 @@ class KNNTransform : public Transform
             QHash<QString, float> votes;
             const int max = (k < 1) ? sortedScores.size() : std::min(k, sortedScores.size());
             for (int j=0; j<max; j++)
-                votes[gallery[sortedScores[j].second].file.get<QString>("Subject")] += (weighted ? sortedScores[j].first : 1);
+                votes[gallery[sortedScores[j].second].file.get<QString>(inputVariable)] += (weighted ? sortedScores[j].first : 1);
             subjects.append(votes.keys()[votes.values().indexOf(Common::Max(votes.values()))]);
 
             // Remove subject from consideration
             if (subjects.size() < numSubjects)
                 for (int j=sortedScores.size()-1; j>=0; j--)
-                    if (gallery[sortedScores[j].second].file.get<QString>("Subject") == subjects.last())
+                    if (gallery[sortedScores[j].second].file.get<QString>(inputVariable) == subjects.last())
                         sortedScores.removeAt(j);
         }
 
-        dst.file.set("KNN", subjects.size() > 1 ? "[" + subjects.join(",") + "]" : subjects.first());
+        dst.file.set(outputVariable, subjects.size() > 1 ? "[" + subjects.join(",") + "]" : subjects.first());
     }
 
     void store(QDataStream &stream) const
diff --git a/openbr/plugins/eigen3.cpp b/openbr/plugins/eigen3.cpp
index 89765db..4a904c2 100644
--- a/openbr/plugins/eigen3.cpp
+++ b/openbr/plugins/eigen3.cpp
@@ -303,10 +303,12 @@ class LDATransform : public Transform
     Q_PROPERTY(bool pcaWhiten READ get_pcaWhiten WRITE set_pcaWhiten RESET reset_pcaWhiten STORED false)
     Q_PROPERTY(int directLDA READ get_directLDA WRITE set_directLDA RESET reset_directLDA STORED false)
     Q_PROPERTY(float directDrop READ get_directDrop WRITE set_directDrop RESET reset_directDrop STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
     BR_PROPERTY(float, pcaKeep, 0.98)
     BR_PROPERTY(bool, pcaWhiten, false)
     BR_PROPERTY(int, directLDA, 0)
     BR_PROPERTY(float, directDrop, 0.1)
+    BR_PROPERTY(QString, inputVariable, "Label")
 
     int dimsOut;
     Eigen::VectorXf mean;
@@ -315,7 +317,7 @@ class LDATransform : public Transform
     void train(const TemplateList &_trainingSet)
     {
         // creates "Label"
-        TemplateList trainingSet = TemplateList::relabel(_trainingSet, "Subject");
+        TemplateList trainingSet = TemplateList::relabel(_trainingSet, inputVariable);
 
         int instances = trainingSet.size();
 
diff --git a/openbr/plugins/gallery.cpp b/openbr/plugins/gallery.cpp
index 18f04e0..85a307b 100644
--- a/openbr/plugins/gallery.cpp
+++ b/openbr/plugins/gallery.cpp
@@ -71,7 +71,7 @@ class arffGallery : public Gallery
         }
 
         arffFile.write(qPrintable(OpenCVUtils::matrixToStringList(t).join(',')));
-        arffFile.write(qPrintable(",'" + t.file.get<QString>("Subject") + "'\n"));
+        arffFile.write(qPrintable(",'" + t.file.get<QString>("Label") + "'\n"));
     }
 };
 
@@ -643,11 +643,16 @@ class dbGallery : public Gallery
             query = query.mid(1, query.size()-2);
         if (!q.exec(query))
             qFatal("%s.", qPrintable(q.lastError().text()));
+
         if ((q.record().count() == 0) || (q.record().count() > 3))
             qFatal("Query record expected one to three fields, got %d.", q.record().count());
         const bool hasMetadata = (q.record().count() >= 2);
         const bool hasFilter = (q.record().count() >= 3);
 
+        QString labelName = "Label";
+        if (q.record().count() >= 2)
+            labelName = q.record().fieldName(1);
+
         // subset = seed:subjectMaxSize:numSubjects:subjectMinSize or
         // subset = seed:{Metadata,...,Metadata}:numSubjects
         int seed = 0, subjectMaxSize = std::numeric_limits<int>::max(), numSubjects = std::numeric_limits<int>::max(), subjectMinSize = 0;
@@ -673,6 +678,7 @@ class dbGallery : public Gallery
         QHash<QString, QList<Entry> > entries; // QHash<Label, QList<Entry> >
         while (q.next()) {
             if (hasFilter && (seed >= 0) && (qHash(q.value(2).toString()) % 2 != (uint)seed % 2)) continue; // Ensures training and testing filters don't overlap
+
             if (metadataFields.isEmpty())
                 entries[hasMetadata ? q.value(1).toString() : ""].append(QPair<QString,QString>(q.value(0).toString(), hasFilter ? q.value(2).toString() : ""));
             else
@@ -707,8 +713,10 @@ class dbGallery : public Gallery
 
                 if (entryList.size() > subjectMaxSize)
                     std::random_shuffle(entryList.begin(), entryList.end());
-                foreach (const Entry &entry, entryList.mid(0, subjectMaxSize))
-                    templates.append(File(entry.first, label));
+                foreach (const Entry &entry, entryList.mid(0, subjectMaxSize)) {
+                    templates.append(File(entry.first));
+                    templates.last().file.set(labelName, label);
+                }
                 numSubjects--;
             }
         }
@@ -816,7 +824,7 @@ class statGallery : public Gallery
 
     void write(const Template &t)
     {
-        subjects.insert(t.file.get<QString>("Subject"));
+        subjects.insert(t.file.get<QString>("Label"));
         bytes.append(t.bytes());
     }
 };
diff --git a/openbr/plugins/independent.cpp b/openbr/plugins/independent.cpp
index 123c979..4a1ec03 100644
--- a/openbr/plugins/independent.cpp
+++ b/openbr/plugins/independent.cpp
@@ -9,37 +9,36 @@ using namespace cv;
 namespace br
 {
 
-static TemplateList Downsample(const TemplateList &templates, const Transform *transform)
+static TemplateList Downsample(const TemplateList &templates, int classes, int instances, float fraction, const QString & inputVariable)
 {
     // Return early when no downsampling is required
-    if ((transform->classes == std::numeric_limits<int>::max()) &&
-            (transform->instances == std::numeric_limits<int>::max()) &&
-            (transform->fraction >= 1))
+    if ((classes == std::numeric_limits<int>::max()) &&
+            (instances == std::numeric_limits<int>::max()) &&
+            (fraction >= 1))
         return templates;
 
-    const bool atLeast = transform->instances < 0;
-    const int instances = abs(transform->instances);
+    const bool atLeast = instances < 0;
+    instances = abs(instances);
 
-    QList<QString> allLabels = File::get<QString>(templates, "Subject");
+    QList<QString> allLabels = File::get<QString>(templates, inputVariable);
     QList<QString> uniqueLabels = allLabels.toSet().toList();
     qSort(uniqueLabels);
 
-    QMap<QString,int> counts = templates.countValues<QString>("Subject", instances != std::numeric_limits<int>::max());
+    QMap<QString,int> counts = templates.countValues<QString>(inputVariable, instances != std::numeric_limits<int>::max());
 
-    if ((instances != std::numeric_limits<int>::max()) && (transform->classes != std::numeric_limits<int>::max()))
+    if ((instances != std::numeric_limits<int>::max()) && (classes != std::numeric_limits<int>::max()))
         foreach (const QString & label, counts.keys())
             if (counts[label] < instances)
                 counts.remove(label);
 
     uniqueLabels = counts.keys();
-    if ((transform->classes != std::numeric_limits<int>::max()) && (uniqueLabels.size() < transform->classes))
-        qWarning("Downsample requested %d classes but only %d are available.", transform->classes, uniqueLabels.size());
+    if ((classes != std::numeric_limits<int>::max()) && (uniqueLabels.size() < classes))
+        qWarning("Downsample requested %d classes but only %d are available.", classes, uniqueLabels.size());
 
-    Common::seedRNG();
     QList<QString> selectedLabels = uniqueLabels;
-    if (transform->classes < uniqueLabels.size()) {
+    if (classes < uniqueLabels.size()) {
         std::random_shuffle(selectedLabels.begin(), selectedLabels.end());
-        selectedLabels = selectedLabels.mid(0, transform->classes);
+        selectedLabels = selectedLabels.mid(0, classes);
     }
 
     TemplateList downsample;
@@ -56,14 +55,45 @@ static TemplateList Downsample(const TemplateList &templates, const Transform *t
             downsample.append(templates.value(indices[j]));
     }
 
-    if (transform->fraction < 1) {
+    if (fraction < 1) {
         std::random_shuffle(downsample.begin(), downsample.end());
-        downsample = downsample.mid(0, downsample.size()*transform->fraction);
+        downsample = downsample.mid(0, downsample.size()*fraction);
     }
 
     return downsample;
 }
 
+class DownsampleTrainingTransform : public Transform
+{
+    Q_OBJECT
+    Q_PROPERTY(br::Transform* transform READ get_transform WRITE set_transform RESET reset_transform STORED true)
+    Q_PROPERTY(int classes READ get_classes WRITE set_classes RESET reset_classes STORED false)
+    Q_PROPERTY(int instances READ get_instances WRITE set_instances RESET reset_instances STORED false)
+    Q_PROPERTY(float fraction READ get_fraction WRITE set_fraction RESET reset_fraction STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
+    BR_PROPERTY(br::Transform*, transform, NULL)
+    BR_PROPERTY(int, classes, std::numeric_limits<int>::max())
+    BR_PROPERTY(int, instances, std::numeric_limits<int>::max())
+    BR_PROPERTY(float, fraction, 1)
+    BR_PROPERTY(QString, inputVariable, "Label")
+
+    void project(const Template & src, Template & dst) const
+    {
+       transform->project(src,dst);      
+    }
+  
+	  
+    void train(const TemplateList &data)
+    {
+        if (!transform || !transform->trainable)
+            return;
+
+        TemplateList downsampled = Downsample(data, classes, instances, fraction, inputVariable);
+        transform->train(downsampled);
+    }
+};
+BR_REGISTER(Transform, DownsampleTrainingTransform)
+
 /*!
  * \ingroup transforms
  * \brief Clones the transform so that it can be applied independently.
@@ -124,13 +154,10 @@ class IndependentTransform : public MetaTransform
         while (transforms.size() < templatesList.size())
             transforms.append(transform->clone());
 
-        for (int i=0; i<templatesList.size(); i++)
-            templatesList[i] = Downsample(templatesList[i], transforms[i]);
-
         QFutureSynchronizer<void> futures;
         for (int i=0; i<templatesList.size(); i++)
-            futures.addFuture(QtConcurrent::run(_train, transforms[i], &templatesList[i]));
-        futures.waitForFinished();
+	  futures.addFuture(QtConcurrent::run(_train, transforms[i], &templatesList[i]));
+	futures.waitForFinished();
     }
 
     void project(const Template &src, Template &dst) const
diff --git a/openbr/plugins/mask.cpp b/openbr/plugins/mask.cpp
index 8b86221..81fa8fb 100644
--- a/openbr/plugins/mask.cpp
+++ b/openbr/plugins/mask.cpp
@@ -158,6 +158,9 @@ class LargestConvexAreaTransform : public UntrainableTransform
 {
     Q_OBJECT
 
+    Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false)
+    BR_PROPERTY(QString, outputVariable, "Label")
+
     void project(const Template &src, Template &dst) const
     {
         std::vector< std::vector<Point> > contours;
@@ -171,7 +174,7 @@ class LargestConvexAreaTransform : public UntrainableTransform
             if (area / hullArea > 0.98)
                 maxArea = std::max(maxArea, area);
         }
-        dst.file.set("Label", maxArea);
+        dst.file.set(outputVariable, maxArea);
     }
 };
 
diff --git a/openbr/plugins/normalize.cpp b/openbr/plugins/normalize.cpp
index 5c85415..842e952 100644
--- a/openbr/plugins/normalize.cpp
+++ b/openbr/plugins/normalize.cpp
@@ -97,6 +97,7 @@ class CenterTransform : public Transform
     Q_OBJECT
     Q_ENUMS(Method)
     Q_PROPERTY(Method method READ get_method WRITE set_method RESET reset_method STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
 
 public:
     /*!< */
@@ -107,6 +108,7 @@ public:
 
 private:
     BR_PROPERTY(Method, method, Mean)
+    BR_PROPERTY(QString, inputVariable, "Label")
 
     Mat a, b; // dst = (src - b) / a
 
@@ -127,7 +129,7 @@ private:
         Mat m;
         OpenCVUtils::toMat(data.data()).convertTo(m, CV_64F);
 
-        const QList<int> labels = data.indexProperty("Subject");
+        const QList<int> labels = data.indexProperty(inputVariable);
         const int dims = m.cols;
 
         vector<Mat> mv, av, bv;
diff --git a/openbr/plugins/openbr_internal.h b/openbr/plugins/openbr_internal.h
index 2f42e50..27136da 100644
--- a/openbr/plugins/openbr_internal.h
+++ b/openbr/plugins/openbr_internal.h
@@ -219,10 +219,6 @@ public:
         }
 
         output->file = this->file;
-        output->classes = classes;
-        output->instances = instances;
-        output->fraction = fraction;
-
         output->init();
 
         return output;
diff --git a/openbr/plugins/output.cpp b/openbr/plugins/output.cpp
index 2b75582..e71adc1 100644
--- a/openbr/plugins/output.cpp
+++ b/openbr/plugins/output.cpp
@@ -146,8 +146,8 @@ class meltOutput : public MatrixOutput
         QStringList lines;
         if (file.baseName() != "terminal") lines.append(QString("Query,Target,Mask,Similarity%1").arg(keys));
 
-        QList<QString> queryLabels = File::get<QString>(queryFiles, "Subject");
-        QList<QString> targetLabels = File::get<QString>(targetFiles, "Subject");
+        QList<QString> queryLabels = File::get<QString>(queryFiles, "Label");
+        QList<QString> targetLabels = File::get<QString>(targetFiles, "Label");
 
         for (int i=0; i<queryFiles.size(); i++) {
             for (int j=(selfSimilar ? i+1 : 0); j<targetFiles.size(); j++) {
@@ -298,7 +298,7 @@ class txtOutput : public MatrixOutput
         if (file.isNull() || targetFiles.isEmpty() || queryFiles.isEmpty()) return;
         QStringList lines;
         foreach (const File &file, queryFiles)
-            lines.append(file.name + " " + file.get<QString>("Subject"));
+            lines.append(file.name + " " + file.get<QString>("Label"));
         QtUtils::writeFile(file, lines);
     }
 };
@@ -428,7 +428,7 @@ class rankOutput : public MatrixOutput
             foreach (const Pair &pair, Common::Sort(OpenCVUtils::matrixToVector<float>(data.row(i)), true)) {
                 if (Globals->crossValidate > 0 ? (targetFiles[pair.second].get<int>("Partition",-1) == queryFiles[i].get<int>("Partition",-1)) : true) {
                     if (QString(targetFiles[pair.second]) != QString(queryFiles[i])) {
-                        if (targetFiles[pair.second].get<QString>("Subject") == queryFiles[i].get<QString>("Subject")) {
+                        if (targetFiles[pair.second].get<QString>("Label") == queryFiles[i].get<QString>("Label")) {
                             ranks.append(rank);
                             positions.append(pair.second);
                             scores.append(pair.first);
diff --git a/openbr/plugins/quality.cpp b/openbr/plugins/quality.cpp
index fd3209c..e372460 100644
--- a/openbr/plugins/quality.cpp
+++ b/openbr/plugins/quality.cpp
@@ -19,17 +19,20 @@ class ImpostorUniquenessMeasureTransform : public Transform
     Q_PROPERTY(br::Distance* distance READ get_distance WRITE set_distance RESET reset_distance STORED false)
     Q_PROPERTY(double mean READ get_mean WRITE set_mean RESET reset_mean)
     Q_PROPERTY(double stddev READ get_stddev WRITE set_stddev RESET reset_stddev)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
     BR_PROPERTY(br::Distance*, distance, Distance::make("Dist(L2)", this))
     BR_PROPERTY(double, mean, 0)
     BR_PROPERTY(double, stddev, 1)
+    BR_PROPERTY(QString, inputVariable, "Label")
+
     TemplateList impostors;
 
     float calculateIUM(const Template &probe, const TemplateList &gallery) const
     {
-        const QString probeLabel = probe.file.get<QString>("Subject");
+        const QString probeLabel = probe.file.get<QString>(inputVariable);
         TemplateList subset = gallery;
         for (int j=subset.size()-1; j>=0; j--)
-            if (subset[j].file.get<QString>("Subject") == probeLabel)
+            if (subset[j].file.get<QString>(inputVariable) == probeLabel)
                 subset.removeAt(j);
 
         QList<float> scores = distance->compare(subset, probe);
@@ -151,6 +154,7 @@ class MatchProbabilityDistance : public Distance
     Q_PROPERTY(br::Distance* distance READ get_distance WRITE set_distance RESET reset_distance STORED false)
     Q_PROPERTY(bool gaussian READ get_gaussian WRITE set_gaussian RESET reset_gaussian STORED false)
     Q_PROPERTY(bool crossModality READ get_crossModality WRITE set_crossModality RESET reset_crossModality STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
 
     MP mp;
 
@@ -158,7 +162,7 @@ class MatchProbabilityDistance : public Distance
     {
         distance->train(src);
 
-        const QList<int> labels = src.indexProperty("Subject");
+        const QList<int> labels = src.indexProperty(inputVariable);
         QScopedPointer<MatrixOutput> matrixOutput(MatrixOutput::make(FileList(src.size()), FileList(src.size())));
         distance->compare(src, src, matrixOutput.data());
 
@@ -201,6 +205,7 @@ protected:
     BR_PROPERTY(br::Distance*, distance, make("Dist(L2)"))
     BR_PROPERTY(bool, gaussian, true)
     BR_PROPERTY(bool, crossModality, false)
+    BR_PROPERTY(QString, inputVariable, "Label")
 };
 
 BR_REGISTER(Distance, MatchProbabilityDistance)
@@ -217,10 +222,12 @@ class HeatMapDistance : public Distance
     Q_PROPERTY(bool gaussian READ get_gaussian WRITE set_gaussian RESET reset_gaussian STORED false)
     Q_PROPERTY(bool crossModality READ get_crossModality WRITE set_crossModality RESET reset_crossModality STORED false)
     Q_PROPERTY(int step READ get_step WRITE set_step RESET reset_step STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
     BR_PROPERTY(br::Distance*, distance, make("Dist(L2)"))
     BR_PROPERTY(bool, gaussian, true)
     BR_PROPERTY(bool, crossModality, false)
     BR_PROPERTY(int, step, 1)
+    BR_PROPERTY(QString, inputVariable, "Label")
 
     QList<MP> mp;
 
@@ -228,7 +235,7 @@ class HeatMapDistance : public Distance
     {
         distance->train(src);
 
-        const QList<int> labels = src.indexProperty("Subject");
+        const QList<int> labels = src.indexProperty(inputVariable);
 
         QList<TemplateList> patches;
 
@@ -307,14 +314,16 @@ class UnitDistance : public Distance
     Q_PROPERTY(br::Distance *distance READ get_distance WRITE set_distance RESET reset_distance)
     Q_PROPERTY(float a READ get_a WRITE set_a RESET reset_a)
     Q_PROPERTY(float b READ get_b WRITE set_b RESET reset_b)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
     BR_PROPERTY(br::Distance*, distance, make("Dist(L2)"))
     BR_PROPERTY(float, a, 1)
     BR_PROPERTY(float, b, 0)
+    BR_PROPERTY(QString, inputVariable, "Label")
 
     void train(const TemplateList &templates)
     {
         const TemplateList samples = templates.mid(0, 2000);
-        const QList<int> sampleLabels = samples.indexProperty("Subject");
+        const QList<int> sampleLabels = samples.indexProperty(inputVariable);
         QScopedPointer<MatrixOutput> matrixOutput(MatrixOutput::make(FileList(samples.size()), FileList(samples.size())));
         Distance::compare(samples, samples, matrixOutput.data());
 
diff --git a/openbr/plugins/quantize.cpp b/openbr/plugins/quantize.cpp
index 94840f6..e74513f 100644
--- a/openbr/plugins/quantize.cpp
+++ b/openbr/plugins/quantize.cpp
@@ -120,6 +120,10 @@ BR_REGISTER(Transform, HistEqQuantizationTransform)
 class BayesianQuantizationDistance : public Distance
 {
     Q_OBJECT
+
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
+    BR_PROPERTY(QString, inputVariable, "Label")
+
     QVector<float> loglikelihoods;
 
     static void computeLogLikelihood(const Mat &data, const QList<int> &labels, float *loglikelihood)
@@ -150,7 +154,7 @@ class BayesianQuantizationDistance : public Distance
             qFatal("Expected sigle matrix templates of type CV_8UC1!");
 
         const Mat data = OpenCVUtils::toMat(src.data());
-        const QList<int> templateLabels = src.indexProperty("Subject");
+        const QList<int> templateLabels = src.indexProperty(inputVariable);
         loglikelihoods = QVector<float>(data.cols*256, 0);
 
         QFutureSynchronizer<void> futures;
@@ -343,9 +347,11 @@ class ProductQuantizationTransform : public Transform
     Q_PROPERTY(int n READ get_n WRITE set_n RESET reset_n STORED false)
     Q_PROPERTY(br::Distance *distance READ get_distance WRITE set_distance RESET reset_distance STORED false)
     Q_PROPERTY(bool bayesian READ get_bayesian WRITE set_bayesian RESET reset_bayesian STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
     BR_PROPERTY(int, n, 2)
     BR_PROPERTY(br::Distance*, distance, Distance::make("L2", this))
     BR_PROPERTY(bool, bayesian, false)
+    BR_PROPERTY(QString, inputVariable, "Label")
 
     quint16 index;
     QList<Mat> centers;
@@ -474,7 +480,7 @@ private:
         Mat data = OpenCVUtils::toMat(src.data());
         const int step = getStep(data.cols);
 
-        const QList<int> labels = src.indexProperty("Subject");
+        const QList<int> labels = src.indexProperty(inputVariable);
 
         Mat &lut = ProductQuantizationLUTs[index];
         lut = Mat(getDims(data.cols), 256*(256+1)/2, CV_32FC1);
diff --git a/openbr/plugins/quantize2.cpp b/openbr/plugins/quantize2.cpp
index 63ea769..8d05523 100644
--- a/openbr/plugins/quantize2.cpp
+++ b/openbr/plugins/quantize2.cpp
@@ -19,6 +19,10 @@ namespace br
 class BayesianQuantizationTransform : public Transform
 {
     Q_OBJECT
+
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
+    BR_PROPERTY(QString, inputVariable, "Label")
+
     QVector<float> thresholds;
 
     static void computeThresholdsRecursive(const QVector<int> &cumulativeGenuines, const QVector<int> &cumulativeImpostors,
@@ -77,7 +81,7 @@ class BayesianQuantizationTransform : public Transform
     void train(const TemplateList &src)
     {
         const Mat data = OpenCVUtils::toMat(src.data());
-        const QList<int> labels = src.indexProperty("Subject");
+        const QList<int> labels = src.indexProperty(inputVariable);
 
         thresholds = QVector<float>(256*data.cols);
 
diff --git a/openbr/plugins/svm.cpp b/openbr/plugins/svm.cpp
index 39efa4d..d4e2aad 100644
--- a/openbr/plugins/svm.cpp
+++ b/openbr/plugins/svm.cpp
@@ -101,6 +101,8 @@ class SVMTransform : public Transform
     Q_PROPERTY(Type type READ get_type WRITE set_type RESET reset_type STORED false)
     Q_PROPERTY(float C READ get_C WRITE set_C RESET reset_C STORED false)
     Q_PROPERTY(float gamma READ get_gamma WRITE set_gamma RESET reset_gamma STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
+    Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false)
 
 public:
     enum Kernel { Linear = CvSVM::LINEAR,
@@ -119,6 +121,9 @@ private:
     BR_PROPERTY(Type, type, C_SVC)
     BR_PROPERTY(float, C, -1)
     BR_PROPERTY(float, gamma, -1)
+    BR_PROPERTY(QString, inputVariable, "")
+    BR_PROPERTY(QString, outputVariable, "")
+
 
     SVM svm;
     QHash<QString, int> labelMap;
@@ -128,14 +133,15 @@ private:
     {
         Mat data = OpenCVUtils::toMat(_data.data());
         Mat lab;
-        // If we are doing regression, assume subject has float values
+        // If we are doing regression, the input variable should have float
+	// values
         if (type == EPS_SVR || type == NU_SVR) {
-            lab = OpenCVUtils::toMat(File::get<float>(_data, "Subject"));
+            lab = OpenCVUtils::toMat(File::get<float>(_data, inputVariable));
         }
-        // If we are doing classification, assume subject has discrete values, map them
-        // and store the mapping data
+        // If we are doing classification, we should be dealing with discrete
+	// values. Map them and store the mapping data
         else {
-            QList<int> dataLabels = _data.indexProperty("Subject", labelMap, reverseLookup);
+            QList<int> dataLabels = _data.indexProperty(inputVariable, labelMap, reverseLookup);
             lab = OpenCVUtils::toMat(dataLabels);
         }
         trainSVM(svm, data, lab, kernel, type, C, gamma);
@@ -146,9 +152,9 @@ private:
         dst = src;
         float prediction = svm.predict(src.m().reshape(1, 1));
         if (type == EPS_SVR || type == NU_SVR)
-            dst.file.set("Subject", prediction);
+            dst.file.set(outputVariable, prediction);
         else
-            dst.file.set("Subject", reverseLookup[prediction]);
+            dst.file.set(outputVariable, reverseLookup[prediction]);
     }
 
     void store(QDataStream &stream) const
@@ -162,6 +168,24 @@ private:
         loadSVM(svm, stream);
         stream >> labelMap >> reverseLookup;
     }
+
+    void init()
+    {
+        // Since SVM can do regression or classification, we have to check the problem type before
+        // specifying target variable names
+        if (inputVariable.isEmpty())
+        {
+            if (type == EPS_SVR || type == NU_SVR) {
+                inputVariable = "Regressor";
+                if (outputVariable.isEmpty())
+                    outputVariable = "Regressand";
+            }
+            else
+                inputVariable = "Label";
+        }
+        if (outputVariable.isEmpty())
+            outputVariable = inputVariable;
+    }
 };
 
 BR_REGISTER(Transform, SVMTransform)
@@ -178,6 +202,8 @@ class SVMDistance : public Distance
     Q_ENUMS(Type)
     Q_PROPERTY(Kernel kernel READ get_kernel WRITE set_kernel RESET reset_kernel STORED false)
     Q_PROPERTY(Type type READ get_type WRITE set_type RESET reset_type STORED false)
+    Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
+
 
 public:
     enum Kernel { Linear = CvSVM::LINEAR,
@@ -194,13 +220,14 @@ public:
 private:
     BR_PROPERTY(Kernel, kernel, Linear)
     BR_PROPERTY(Type, type, EPS_SVR)
+    BR_PROPERTY(QString, inputVariable, "Label")
 
     SVM svm;
 
     void train(const TemplateList &src)
     {
         const Mat data = OpenCVUtils::toMat(src.data());
-        const QList<int> lab = src.indexProperty("Subject");
+        const QList<int> lab = src.indexProperty(inputVariable);
 
         const int instances = data.rows * (data.rows+1) / 2;
         Mat deltaData(instances, data.cols, data.type());
diff --git a/scripts/evalAgeRegression-PCSO.sh b/scripts/evalAgeRegression-PCSO.sh
index 8d0f286..9e294fe 100755
--- a/scripts/evalAgeRegression-PCSO.sh
+++ b/scripts/evalAgeRegression-PCSO.sh
@@ -4,8 +4,12 @@ if [ ! -f evalAgeRegression-PCSO.sh ]; then
   exit
 fi
 
+export BR="../build/app/br/br -useGui 0"
+export PCSO_DIR=/user/pripshare/Databases/FaceDatabases/PCSO/PCSO/
+export ageAlg=AgeRegression
+
 # Create a file list by querying the database
-br -quiet -algorithm Identity -enroll "../data/PCSO/PCSO.db[query='SELECT File,Age,PersonID FROM PCSO WHERE Age >= 15 AND AGE <= 75', subset=1:200]" terminal.txt > Input.txt
+$BR -quiet -algorithm Identity -enroll "$PCSO_DIR/PCSO.db[query='SELECT File,Age,PersonID FROM PCSO WHERE Age >= 17 AND AGE <= 68', subset=1:200]" terminal.txt > Input.txt
 
 # Enroll the file list and evaluate performance
-br -algorithm AgeRegression -path ../data/PCSO/img -enroll Input.txt Output.txt -evalRegression Output.txt Input.txt
+$BR -algorithm $ageAlg  -path $PCSO_DIR/Images -enroll Input.txt Output.txt -evalRegression Output.txt Input.txt Age
diff --git a/scripts/evalFaceRecognition-MEDS.sh b/scripts/evalFaceRecognition-MEDS.sh
index 231370f..673f674 100755
--- a/scripts/evalFaceRecognition-MEDS.sh
+++ b/scripts/evalFaceRecognition-MEDS.sh
@@ -20,11 +20,11 @@ if [ ! -e Algorithm_Dataset ]; then
 fi
 
 if [ ! -e MEDS.mask ]; then
-  br -makeMask ../data/MEDS/sigset/MEDS_frontal_target.xml ../data/MEDS/sigset/MEDS_frontal_query.xml MEDS.mask
+  br -useGui 0 -makeMask ../data/MEDS/sigset/MEDS_frontal_target.xml ../data/MEDS/sigset/MEDS_frontal_query.xml MEDS.mask
 fi
 
 # Run Algorithm on MEDS
-br -algorithm ${ALGORITHM} -path ../data/MEDS/img -compare ../data/MEDS/sigset/MEDS_frontal_target.xml ../data/MEDS/sigset/MEDS_frontal_query.xml ${ALGORITHM}_MEDS.mtx -eval ${ALGORITHM}_MEDS.mtx MEDS.mask Algorithm_Dataset/${ALGORITHM}_MEDS.csv
+br -useGui 0 -algorithm ${ALGORITHM} -path ../data/MEDS/img -compare ../data/MEDS/sigset/MEDS_frontal_target.xml ../data/MEDS/sigset/MEDS_frontal_query.xml ${ALGORITHM}_MEDS.mtx -eval ${ALGORITHM}_MEDS.mtx MEDS.mask Algorithm_Dataset/${ALGORITHM}_MEDS.csv
 
 # Plot results
-br -plot Algorithm_Dataset/*_MEDS.csv MEDS
+br -useGui 0 -plot Algorithm_Dataset/*_MEDS.csv MEDS
diff --git a/scripts/evalGenderClassification-PCSO.sh b/scripts/evalGenderClassification-PCSO.sh
index 881214e..9373645 100755
--- a/scripts/evalGenderClassification-PCSO.sh
+++ b/scripts/evalGenderClassification-PCSO.sh
@@ -4,8 +4,13 @@ if [ ! -f evalGenderClassification-PCSO.sh ]; then
   exit
 fi
 
+export BR=../build/app/br/br
+export genderAlg=GenderClassification
+
+export PCSO_DIR=/user/pripshare/Databases/FaceDatabases/PCSO/PCSO/
+
 # Create a file list by querying the database
-br -quiet -algorithm Identity -enroll "../data/PCSO/PCSO.db[query='SELECT File,Gender,PersonID FROM PCSO', subset=1:8000]" terminal.txt > Input.txt
+$BR -useGui 0 -quiet -algorithm Identity -enroll "$PCSO_DIR/PCSO.db[query='SELECT File,Gender,PersonID FROM PCSO', subset=1:8000]" terminal.txt > Input.txt
 
 # Enroll the file list and evaluate performance
-br -algorithm GenderClassification -path ../data/PCSO/img -enroll Input.txt Output.txt -evalClassification Output.txt Input.txt
+$BR -useGui 0  -algorithm $genderAlg -path $PCSO_DIR/Images -enroll Input.txt Output.txt -evalClassification Output.txt Input.txt Gender
\ No newline at end of file
diff --git a/scripts/trainAgeRegression-PCSO.sh b/scripts/trainAgeRegression-PCSO.sh
index c063055..c1f3ef1 100755
--- a/scripts/trainAgeRegression-PCSO.sh
+++ b/scripts/trainAgeRegression-PCSO.sh
@@ -6,6 +6,11 @@ fi
 
 #rm -f ../share/openbr/models/features/FaceClassificationRegistration
 #rm -f ../share/openbr/models/features/FaceClassificationExtraction
-rm -f ../share/openbr/models/algorithms/AgeRegression
+#rm -f ../share/openbr/models/algorithms/AgeRegression
 
-br -algorithm AgeRegression -path ../data/PCSO/Images -train "../data/PCSO/PCSO.db[query='SELECT File,Age,PersonID FROM PCSO WHERE Age >= 15 AND AGE <= 75', subset=0:200]" ../share/openbr/models/algorithms/AgeRegression
+export BR=../build/app/br/br
+export ageAlg=AgeRegression
+
+export PCSO_DIR=/user/pripshare/Databases/FaceDatabases/PCSO/PCSO/
+
+$BR -useGui 0 -algorithm $ageAlg -path $PCSO_DIR/Images -train "$PCSO_DIR/PCSO.db[query='SELECT File,Age,PersonID FROM PCSO WHERE Age >= 17 AND AGE <= 68', subset=0:200]" ../share/openbr/models/algorithms/AgeRegression
diff --git a/scripts/trainFaceRecognition-PCSO.sh b/scripts/trainFaceRecognition-PCSO.sh
index e67b3aa..ebeb056 100755
--- a/scripts/trainFaceRecognition-PCSO.sh
+++ b/scripts/trainFaceRecognition-PCSO.sh
@@ -8,6 +8,13 @@ fi
 #rm -f ../share/openbr/models/features/FaceRecognitionExtraction
 #rm -f ../share/openbr/models/features/FaceRecognitionEmbedding
 #rm -f ../share/openbr/models/features/FaceRecognitionQuantization
-rm -f ../share/openbr/models/algorithms/FaceRecognition
+#rm -f ../share/openbr/models/algorithms/FaceRecognition
+
+export BR=../build/app/br/br
+
+export PCSO_DIR=/user/pripshare/Databases/FaceDatabases/PCSO/PCSO/
+
+
+
+$BR -useGui 0 -algorithm FaceRecognition -path "$PCSO_DIR/Images/" -train "$PCSO_DIR/PCSO.db[query='SELECT File,PersonID as Label,PersonID FROM PCSO', subset=0:5:6000]" ../share/openbr/models/algorithms/FaceRecognition
 
-br -algorithm FaceRecognition -path ../data/PCSO/img -train "../data/PCSO/PCSO.db[query='SELECT File,'S'||PersonID,PersonID FROM PCSO', subset=0:5:6000]" ../share/openbr/models/algorithms/FaceRecognition
diff --git a/scripts/trainGenderClassification-PCSO.sh b/scripts/trainGenderClassification-PCSO.sh
index 91fae04..acb8146 100755
--- a/scripts/trainGenderClassification-PCSO.sh
+++ b/scripts/trainGenderClassification-PCSO.sh
@@ -6,6 +6,11 @@ fi
 
 #rm -f ../share/openbr/models/features/FaceClassificationRegistration
 #rm -f ../share/openbr/models/features/FaceClassificationExtraction
-rm -f ../share/openbr/models/algorithms/GenderClassification
+#rm -f ../share/openbr/models/algorithms/GenderClassification
 
-br -algorithm GenderClassification -path ../data/PCSO/Images -train "../data/PCSO/PCSO.db[query='SELECT File,Gender,PersonID FROM PCSO', subset=0:8000]" ../share/openbr/models/algorithms/GenderClassification
+export BR=../build/app/br/br
+export genderAlg=GenderClassification
+
+export PCSO_DIR=/user/pripshare/Databases/FaceDatabases/PCSO/PCSO/
+
+$BR -useGui 0  -algorithm $genderAlg -path $PCSO_DIR/Images -train "$PCSO_DIR/PCSO.db[query='SELECT File,Gender,PersonID FROM PCSO', subset=0:8000]" ../share/openbr/models/algorithms/GenderClassification
diff --git a/share/openbr/models b/share/openbr/models
index dccddf4..a73d510 160000
--- a/share/openbr/models
+++ b/share/openbr/models
@@ -1 +1 @@
-Subproject commit dccddf4dd3a5239911807beeec39308f8890b1e4
+Subproject commit a73d51013ea05f263e88a28539393159fff2183e