GH-15832 Fix UpliftDRF MOJO API, add docs, tests

h2o-algos/src/main/java/hex/generic/Generic.java

@@ -39,6 +39,7 @@ public class Generic extends ModelBuilder<GenericModel, GenericModelParameters,
         allowedAlgos.add("coxph");
         allowedAlgos.add("rulefit");
         allowedAlgos.add("gam");
+        allowedAlgos.add("upliftdrf");
 
         ALLOWED_MOJO_ALGOS = Collections.unmodifiableSet(allowedAlgos);
     }

h2o-algos/src/main/java/hex/generic/GenericModel.java

@@ -108,6 +108,8 @@ public ModelMetrics.MetricBuilder makeMetricBuilder(String[] domain) {
                 return new ModelMetricsRegressionCoxPH.MetricBuilderRegressionCoxPH("start", "stop", false, new String[0]);
             case AnomalyDetection:
                 return new ModelMetricsAnomaly.MetricBuilderAnomaly();
+            case BinomialUplift:
+                return new ModelMetricsBinomialUplift.MetricBuilderBinomialUplift(domain, null);
             default:
                 throw H2O.unimpl();
         }
@@ -181,8 +183,15 @@ private void predict(EasyPredictModelWrapper wrapper, AdaptFrameParameters adapt
             final String offsetColumn = adaptFrameParameters.getOffsetColumn();
             final String weightsColumn = adaptFrameParameters.getWeightsColumn();
             final String responseColumn = adaptFrameParameters.getResponseColumn();
+            final String treatmentColumn = adaptFrameParameters.getTreatmentColumn();
             final boolean isClassifier = wrapper.getModel().isClassifier();
-            final float[] yact = new float[1];
+            final boolean isUplift = treatmentColumn != null;
+            final float[] yact;
+            if (isUplift) {
+                yact = new float[2];
+            } else {
+                yact = new float[1];
+            }
             for (int row = 0; row < cs[0]._len; row++) {
                 RowData rowData = new RowData();
                 RowDataUtils.extractChunkRow(cs, _fr._names, types, row, rowData);
@@ -206,6 +215,9 @@ private void predict(EasyPredictModelWrapper wrapper, AdaptFrameParameters adapt
                         yact[0] = (float) idx;
                     } else 
                         yact[0] = ((Number) response).floatValue();
+                    if (isUplift){
+                        yact[1] = (float) rowData.get(treatmentColumn);
+                    }
                     _mb.perRow(result, yact, weight, offset, GenericModel.this);
                 }
             }
@@ -285,7 +297,7 @@ public String getResponseColumn() {
                 return genModel.isSupervised() ? genModel.getResponseName() : null; 
             }
             @Override
-            public String getTreatmentColumn() {return null;}
+            public String getTreatmentColumn() {return descriptor != null ? descriptor.treatmentColumn() : null;}
             @Override
             public double missingColumnsType() {
                 return Double.NaN;

h2o-algos/src/main/java/hex/generic/GenericModelOutput.java

@@ -5,6 +5,7 @@
 import hex.genmodel.attributes.metrics.*;
 import hex.genmodel.descriptor.ModelDescriptor;
 import hex.tree.isofor.ModelMetricsAnomaly;
+import water.util.ArrayUtils;
 import water.util.Log;
 import water.util.TwoDimTable;
 
@@ -27,6 +28,7 @@ public GenericModelOutput(final ModelDescriptor modelDescriptor) {
         _hasOffset = modelDescriptor.offsetColumn() != null;
         _hasWeights = modelDescriptor.weightsColumn() != null;
         _hasFold = modelDescriptor.foldColumn() != null;
+        _hasTreatment = modelDescriptor.treatmentColumn() != null;
         _modelClassDist = modelDescriptor.modelClassDist();
         _priorClassDist = modelDescriptor.priorClassDist();
         _names = modelDescriptor.columnNames();
@@ -36,6 +38,7 @@ public GenericModelOutput(final ModelDescriptor modelDescriptor) {
         _defaultThreshold = modelDescriptor.defaultThreshold();
         _original_model_identifier = modelDescriptor.algoName();
         _original_model_full_name = modelDescriptor.algoFullName();
+
     }
 
     public GenericModelOutput(final ModelDescriptor modelDescriptor, final ModelAttributes modelAttributes, 
@@ -190,6 +193,15 @@ ordinalMetrics._logloss, customMetric(ordinalMetrics),
                         metricsCoxPH._sigma, metricsCoxPH._mae, metricsCoxPH._root_mean_squared_log_error, metricsCoxPH._mean_residual_deviance,
                         customMetric(mojoMetrics),
                         metricsCoxPH._concordance, metricsCoxPH._concordant, metricsCoxPH._discordant, metricsCoxPH._tied_y);
+            case BinomialUplift:
+                assert mojoMetrics instanceof MojoModelMetricsBinomialUplift;
+                MojoModelMetricsBinomialUplift metricsUplift = (MojoModelMetricsBinomialUplift) mojoMetrics;
+                AUUC.AUUCType auucType = AUUC.AUUCType.valueOf((String) modelAttributes.getParameterValueByName("auuc_type"));
+                AUUC auuc = createAUUC(auucType, metricsUplift._thresholds_and_metric_scores, metricsUplift._auuc_table, metricsUplift._aecu_table);
+                return new ModelMetricsBinomialUpliftGeneric(null, null, metricsUplift._nobs, _domains[_domains.length - 1], 
+                        metricsUplift._ate, metricsUplift._att, metricsUplift._atc, metricsUplift._sigma, auuc, customMetric(metricsUplift), 
+                        convertTable(metricsUplift._thresholds_and_metric_scores), convertTable(metricsUplift._auuc_table), 
+                        convertTable(metricsUplift._aecu_table), metricsUplift._description);
             case Unknown:
             case Clustering:
             case AutoEncoder:
@@ -283,7 +295,7 @@ private static TwoDimTable[] convertTables(final Table[] inputTables) {
         }
         return tables;
     }
-    
+
     private static TwoDimTable convertTable(final Table convertedTable){
         if(convertedTable == null) return null;
         final TwoDimTable table = new TwoDimTable(convertedTable.getTableHeader(), convertedTable.getTableDescription(),
@@ -295,8 +307,77 @@ private static TwoDimTable convertTable(final Table convertedTable){
                 table.set(j, i, convertedTable.getCell(i,j));
             }
         }
-
         return table;
     }
-
+
+    private static AUUC createAUUC(AUUC.AUUCType auucType, Table thresholds_and_metric_scores, Table auuc_table, Table aecu_table){
+        int nbins = thresholds_and_metric_scores.rows();
+        double[] ths = new double[nbins];
+        long[] freq = new long[nbins];
+        AUUC.AUUCType[] auucTypes = AUUC.AUUCType.values();
+        double[][] uplift = new double[auucTypes.length][nbins];
+        double[][] upliftNorm = new double[auucTypes.length][nbins];
+        double[][] upliftRand = new double[auucTypes.length][nbins];
+        double[] auuc = new double[auucTypes.length];
+        double[] auucNorm = new double[auucTypes.length];
+        double[] auucRand = new double[auucTypes.length];
+        double[] aecu = new double[auucTypes.length];
+
+        String[] thrHeader = thresholds_and_metric_scores.getColHeaders();
+        // threshold column index
+        int thrIndex = ArrayUtils.find(thrHeader, "thresholds");
+        int freqIndex = ArrayUtils.find(thrHeader, "n");
+
+        // uplift type indices
+        int[] upliftIndices = new int[auucTypes.length];
+        int[] upliftNormIndices = new int[auucTypes.length];
+        int[] upliftRandIndices = new int[auucTypes.length];
+        for (int i = 1; i < auucTypes.length; i++) {
+            String auucTypeName  =  auucTypes[i].name(); 
+            upliftIndices[i] = ArrayUtils.find(thrHeader, auucTypeName);
+            upliftNormIndices[i] = ArrayUtils.find(thrHeader, auucTypeName+"_normalized");
+            upliftRandIndices[i] = ArrayUtils.find(thrHeader, auucTypeName+"_random");
+            // AUTO setting
+            if(auucTypeName.equals(AUUC.AUUCType.nameAuto())){
+                upliftIndices[0] = upliftIndices[i];
+                upliftNormIndices[0] = upliftNormIndices[i];
+                upliftRandIndices[0] = upliftRandIndices[i];
+            }
+        }
+        // fill thresholds and uplift values from table
+        for (int i = 0; i < thresholds_and_metric_scores.rows(); i++) {
+            ths[i] = (double) thresholds_and_metric_scores.getCell(thrIndex, i);
+            freq[i] = (long) thresholds_and_metric_scores.getCell(freqIndex, i);
+            for (int j = 0; j < auucTypes.length; j++) {
+                uplift[j][i] = (double) thresholds_and_metric_scores.getCell(upliftIndices[j], i);
+                upliftNorm[j][i] = (double) thresholds_and_metric_scores.getCell(upliftNormIndices[j], i);
+                upliftRand[j][i] = (double) thresholds_and_metric_scores.getCell(upliftRandIndices[j], i);
+            }
+        }
+        // fill auuc values and aecu values
+        String[] auucHeader = auuc_table.getColHeaders();
+        String[] aecuHeader = aecu_table.getColHeaders();
+        for (int i = 1; i < auucTypes.length; i++) {
+            AUUC.AUUCType type = auucTypes[i];
+            String auucTypeName = type.name();
+            int colIndex = ArrayUtils.find(auucHeader, auucTypeName);
+            auuc[i] = (double) auuc_table.getCell(colIndex, 0);
+            auucNorm[i] = (double) auuc_table.getCell(colIndex, 1);
+            auucRand[i] = (double) auuc_table.getCell(colIndex, 2);
+            colIndex = ArrayUtils.find(aecuHeader, auucTypeName);
+            aecu[i] = (double) aecu_table.getCell(colIndex, 0);
+            if(auucTypeName.equals(AUUC.AUUCType.nameAuto())){
+                auuc[0] = auuc[i];
+                auucNorm[0] = auucNorm[i];
+                auucRand[0] = auucRand[i];
+                aecu[0] = aecu[i];
+            }
+        }
+        return new AUUC(ths, freq, auuc, auucNorm, auucRand, aecu, auucType, uplift, upliftNorm, upliftRand);
+    }
+
+    @Override
+    public boolean hasTreatment() {
+        return super.hasTreatment();
+    }
 }

h2o-core/src/main/java/hex/AUUC.java

@@ -10,7 +10,6 @@
 import water.fvec.Frame;
 import water.fvec.Vec;
 import water.util.ArrayUtils;
-import water.util.Log;
 
 import java.util.Arrays;
 import java.util.Iterator;
@@ -79,7 +78,6 @@ public AUUC(Vec probs, Vec y, Vec uplift, AUUCType auucType, int nbins) {
     public AUUC(AUUCBuilder bldr, AUUCType auucType) {
         this(bldr, true, auucType);
     }
-
 
     public AUUC(double[] customThresholds, Vec probs, Vec y, Vec uplift, AUUCType auucType) {
         this(new AUUCImpl(customThresholds).doAll(probs, y, uplift)._bldr, auucType);
@@ -205,6 +203,25 @@ public AUUC() {
         _upliftNormalized = new double[AUUCType.values().length][];
         _upliftRandom = new double[AUUCType.values().length][];
     }
+
+    public AUUC(double[] ths, long[] freq, double[] auuc, double[] auucNorm, double[] auucRand, double[] aecu,
+                AUUCType auucType, double[][] uplift, double[][] upliftNorm, double[][] upliftRand) {
+        _nBins = ths.length;
+        _n = freq[freq.length-1];
+        _ths = ths;
+        _frequencyCumsum = freq;
+        _treatment = _control = _yTreatment = _yControl = _frequency = new long[0];
+        _auucs = auuc;
+        _auucsNormalized = auucNorm;
+        _auucsRandom = auucRand;
+        _aecu = aecu;
+        _maxIdx = -1;
+        _auucType = auucType;
+        _auucTypeIndx = getIndexByAUUCType(_auucType);
+        _uplift = uplift;
+        _upliftNormalized = upliftNorm;
+        _upliftRandom = upliftRand;
+    }
 
     public static double[] calculateQuantileThresholds(int groups, Vec preds) {
         Frame fr = null;
@@ -443,19 +460,14 @@ public enum AUUCType {
          *  @return metric value */
         abstract double exec(long treatment, long control, long yTreatment, long yControl );
         public double exec(AUUC auc, int idx) { return exec(auc.treatment(idx),auc.control(idx),auc.yTreatment(idx),auc.yControl(idx)); }
-        
+
         public static final AUUCType[] VALUES = values();
 
-        public static AUUCType fromString(String strRepr) {
-            for (AUUCType tc : AUUCType.values()) {
-                if (tc.toString().equalsIgnoreCase(strRepr)) {
-                    return tc;
-                }
-            }
-            return null;
-        }
+        public static final AUUCType[] VALUES_WITHOUT_AUTO = ArrayUtils.remove(values().clone(), ArrayUtils.find(AUUCType.values(), AUTO));
 
-        public double maxCriterion(AUUC auuc) { return exec(auuc, maxCriterionIdx(auuc)); }
+        public static String nameAuto(){
+            return qini.name();
+        }
 
         /** Convert a criterion into a threshold index that maximizes the criterion
          *  @return Threshold index that maximizes the criterion

h2o-core/src/main/java/hex/Model.java

@@ -1162,6 +1162,7 @@ public String[] features() {
     public String weightsName () { return _hasWeights ?_names[weightsIdx()]:null;}
     public String offsetName  () { return _hasOffset ?_names[offsetIdx()]:null;}
     public String foldName  () { return _hasFold ?_names[foldIdx()]:null;}
+    public String treatmentName() { return _hasTreatment ? _names[treatmentIdx()]: null;}
     public InteractionBuilder interactionBuilder() { return null; }
     // Vec layout is  [c1,c2,...,cn, w?, o?, f?, u?, r]
     // cn are predictor cols, r is response, w is weights, o is offset, f is fold and t is treatment - these are optional
@@ -3469,6 +3470,8 @@ protected class H2OModelDescriptor implements ModelDescriptor {
       @Override
       public String weightsColumn() { return _output.weightsName(); }
       @Override
+      public String treatmentColumn() { return _output.treatmentName(); }
+      @Override
       public String foldColumn() { return _output.foldName(); }
       @Override
       public ModelCategory getModelCategory() { return _output.getModelCategory(); }

h2o-core/src/main/java/hex/ModelMetrics.java

@@ -435,6 +435,7 @@ public double[] perRow(double ds[], float yact[], double weight, double offset,
       assert(weight == 1 && offset == 0);
       return perRow(ds, yact, m);
     }
+
     public void reduce( T mb ) {
       _sumsqe += mb._sumsqe;
       _count += mb._count;

h2o-core/src/main/java/hex/ModelMetricsBinomialUpliftGeneric.java

@@ -0,0 +1,20 @@
+package hex;
+
+import water.fvec.Frame;
+import water.util.TwoDimTable;
+
+public class ModelMetricsBinomialUpliftGeneric extends ModelMetricsBinomialUplift {
+
+
+    public final TwoDimTable _thresholds_and_metric_scores;
+    public final TwoDimTable _auuc_table;
+    public final TwoDimTable _aecu_table;
+
+    public ModelMetricsBinomialUpliftGeneric(Model model, Frame frame, long nobs, String[] domain, double ate, double att, double atc, double sigma, AUUC auuc, CustomMetric customMetric, TwoDimTable thresholds_and_metric_scores, TwoDimTable auuc_table, TwoDimTable aecu_table, final String description) {
+        super(model, frame, nobs, domain, ate, att, atc, sigma, auuc, customMetric);
+        _thresholds_and_metric_scores = thresholds_and_metric_scores;
+        _auuc_table = auuc_table;
+        _aecu_table = aecu_table;
+        _description = description;
+    }
+}

h2o-core/src/main/java/water/api/schemas3/ModelMetricsBinomialUpliftGenericV3.java

@@ -0,0 +1,29 @@
+package water.api.schemas3;
+
+import hex.ModelMetricsBinomialUpliftGeneric;
+
+public class ModelMetricsBinomialUpliftGenericV3<I extends ModelMetricsBinomialUpliftGeneric, S extends ModelMetricsBinomialUpliftGenericV3<I, S>>
+        extends ModelMetricsBinomialUpliftV3<I, S> {
+
+    @Override
+    public S fillFromImpl(ModelMetricsBinomialUpliftGeneric modelMetrics) {
+        super.fillFromImpl(modelMetrics);
+        this.AUUC = modelMetrics._auuc.auuc();
+        this.auuc_normalized = modelMetrics._auuc.auucNormalized();
+        this.ate = modelMetrics.ate();
+        this.att = modelMetrics.att();
+        this.atc = modelMetrics.atc();
+        this.qini = modelMetrics.qini();
+
+        if (modelMetrics._auuc_table != null) { // Possibly overwrites whatever has been set in the ModelMetricsBinomialV3
+            this.auuc_table = new TwoDimTableV3().fillFromImpl(modelMetrics._auuc_table);
+        }
+        if (modelMetrics._aecu_table != null) { // Possibly overwrites whatever has been set in the ModelMetricsBinomialV3
+            this.aecu_table = new TwoDimTableV3().fillFromImpl(modelMetrics._aecu_table);
+        }
+        if (modelMetrics._thresholds_and_metric_scores != null) { // Possibly overwrites whatever has been set in the ModelMetricsBinomialV3
+            this.thresholds_and_metric_scores = new TwoDimTableV3().fillFromImpl(modelMetrics._thresholds_and_metric_scores);
+        }
+        return (S) this;
+    }
+}

h2o-core/src/main/java/water/api/schemas3/ModelMetricsBinomialUpliftV3.java

@@ -57,8 +57,7 @@ public S fillFromImpl(ModelMetricsBinomialUplift modelMetrics) {
             qini = auuc.qini();
             // Fill TwoDimTable
             String[] thresholds = new String[auuc._nBins];
-            AUUCType metrics[] = AUUCType.VALUES;
-            metrics = ArrayUtils.remove(metrics, Arrays.asList(metrics).indexOf(AUUCType.AUTO));
+            AUUCType metrics[] = AUUCType.VALUES_WITHOUT_AUTO;
             int metricsLength = metrics.length;
             long[] n = new long[auuc._nBins];
             double[][] uplift = new double[metricsLength][];
@@ -89,7 +88,7 @@ public S fillFromImpl(ModelMetricsBinomialUplift modelMetrics) {
                 types     [i + 1 + 2 * metricsLength] = "double";
                 formats   [i + 1 + 2 * metricsLength] = "%f";
             }
-            colHeaders[i + 1 + 2 * metricsLength]  = "n"; types[i + 1 + 2 * metricsLength] = "int"; formats[i + 1 + 2 * metricsLength] = "%d";
+            colHeaders[i + 1 + 2 * metricsLength]  = "n"; types[i + 1 + 2 * metricsLength] = "long"; formats[i + 1 + 2 * metricsLength] = "%d";
             colHeaders[i + 2 + 2 * metricsLength]  = "idx"; types[i + 2 + 2 * metricsLength] = "int"; formats[i + 2 + 2 * metricsLength] = "%d";
             TwoDimTable thresholdsByMetrics = new TwoDimTable("Metrics for Thresholds", "Cumulative Uplift metrics for a given percentile", new String[auuc._nBins], colHeaders, types, formats, null );
             for (i = 0; i < auuc._nBins; i++) {

h2o-core/src/main/resources/META-INF/services/water.api.Schema

@@ -72,6 +72,7 @@ water.api.schemas3.ModelMetricsBinomialGLMGenericV3
 water.api.schemas3.ModelMetricsBinomialV3
 water.api.schemas3.ModelMetricsBinomialGenericV3
 water.api.schemas3.ModelMetricsBinomialUpliftV3
+water.api.schemas3.ModelMetricsBinomialUpliftGenericV3
 water.api.schemas3.ModelMetricsClusteringV3
 water.api.schemas3.ModelMetricsHGLMV3
 water.api.schemas3.ModelMetricsHGLMGenericV3

h2o-docs/src/product/data-science/upliftdrf.rst

@@ -13,7 +13,8 @@ The current version of Uplift DRF is based on the implementation of DRF because
 MOJO Support
 ''''''''''''
 
-Uplift DRF currently doesn't support `MOJOs <../save-and-load-model.html#supported-mojos>`__.
+Uplift DRF supports importing and exporting `MOJOs <../save-and-load-model.html#supported-mojos>`__.
+
 
 Uplift DRF demo
 ~~~~~~~~~~~~~~~

h2o-genmodel/src/main/java/hex/genmodel/MojoPipelineWriter.java

@@ -145,6 +145,9 @@ public String foldColumn() {
       return null;
     }
 
+    @Override
+    public String treatmentColumn() { return null; }
+
     @Override
     public ModelCategory getModelCategory() {
       return _finalModel._category;

h2o-genmodel/src/main/java/hex/genmodel/attributes/ModelAttributes.java

@@ -91,6 +91,8 @@ private static MojoModelMetrics determineModelMetricsType(final MojoModel mojoMo
         } else return new MojoModelMetricsOrdinal();
       case CoxPH:
         return new MojoModelMetricsRegressionCoxPH();
+      case BinomialUplift:
+        return new MojoModelMetricsBinomialUplift();
       case Unknown:
       case Clustering:
       case AutoEncoder: