Dataset<Row> dataFrame = TreeTests.setMetadata(data, categoricalFeatures, 0); GBTRegressor rf = new GBTRegressor() .setMaxDepth(2) .setMaxBins(10) .setMinInstancesPerNode(5) .setMinInfoGain(0.0) .setMaxMemoryInMB(256) .setCacheNodeIds(false) .setCheckpointInterval(10) .setSubsamplingRate(1.0) .setSeed(1234) .setMaxIter(3) .setStepSize(0.1) .setMaxDepth(2); // duplicate setMaxDepth to check builder pattern for (String lossType : GBTRegressor.supportedLossTypes()) { rf.setLossType(lossType); GBTRegressionModel model = rf.fit(dataFrame);
Dataset<Row> dataFrame = TreeTests.setMetadata(data, categoricalFeatures, 0); GBTRegressor rf = new GBTRegressor() .setMaxDepth(2) .setMaxBins(10) .setMinInstancesPerNode(5) .setMinInfoGain(0.0) .setMaxMemoryInMB(256) .setCacheNodeIds(false) .setCheckpointInterval(10) .setSubsamplingRate(1.0) .setSeed(1234) .setMaxIter(3) .setStepSize(0.1) .setMaxDepth(2); // duplicate setMaxDepth to check builder pattern for (String lossType : GBTRegressor.supportedLossTypes()) { rf.setLossType(lossType); GBTRegressionModel model = rf.fit(dataFrame);
Dataset<Row> dataFrame = TreeTests.setMetadata(data, categoricalFeatures, 0); GBTRegressor rf = new GBTRegressor() .setMaxDepth(2) .setMaxBins(10) .setMinInstancesPerNode(5) .setMinInfoGain(0.0) .setMaxMemoryInMB(256) .setCacheNodeIds(false) .setCheckpointInterval(10) .setSubsamplingRate(1.0) .setSeed(1234) .setMaxIter(3) .setStepSize(0.1) .setMaxDepth(2); // duplicate setMaxDepth to check builder pattern for (String lossType : GBTRegressor.supportedLossTypes()) { rf.setLossType(lossType); GBTRegressionModel model = rf.fit(dataFrame);