Package hex.genmodel.easy

The easy prediction API for generated POJO and MOJO models.

See: Description

Class Summary

Class	Description
DomainMapConstructor	Create map from input variable domain information.
EasyPredictModelWrapper	An easy-to-use prediction wrapper for generated models.
EasyPredictModelWrapper.Config	Configuration builder for instantiating a Wrapper.
EasyPredictModelWrapper.ErrorConsumer	Observer interface with methods corresponding to errors during the prediction.
RowData	Column name to column value mapping for a new row (aka data point, observation, sample) to predict.
RowToRawDataConverter	This class is intended to transform a RowData instance - for which we want to get prediction to - into a raw array

Package hex.genmodel.easy Description

The easy prediction API for generated POJO and MOJO models. Use as follows:

1. Instantiate an EasyPredictModelWrapper
2. Create a new row of data
3. Call one of the predict methods

Here is an example:

      // Step 1.   modelClassName = "your_pojo_model_downloaded_from_h2o";   GenModel rawModel;   rawModel = (GenModel) Class.forName(modelClassName).newInstance();   EasyPredictModelWrapper model = new EasyPredictModelWrapper(rawModel);   //   // By default, unknown categorical levels throw PredictUnknownCategoricalLevelException.   // Optionally configure the wrapper to treat unknown categorical levels as N/A instead:   //   //     EasyPredictModelWrapper model = new EasyPredictModelWrapper(   //                                         new EasyPredictModelWrapper.Config()   //                                             .setModel(rawModel)   //                                             .setConvertUnknownCategoricalLevelsToNa(true));   // Step 2.   RowData row = new RowData();   row.put(new String("CategoricalColumnName"), new String("LevelName"));   row.put(new String("NumericColumnName1"), new String("42.0"));   row.put(new String("NumericColumnName2"), new Double(42.0));   // Step 3.   BinomialModelPrediction p = model.predictBinomial(row);