@Override public MiningModel encodeMiningModel(List<RegTree> regTrees, float base_score, Integer ntreeLimit, Schema schema){ Schema segmentSchema = schema.toAnonymousSchema(); MiningModel miningModel = createMiningModel(regTrees, base_score, ntreeLimit, segmentSchema) .setOutput(ModelUtil.createPredictedOutput(FieldName.create("xgbValue"), OpType.CONTINUOUS, DataType.FLOAT)); return MiningModelUtil.createRegression(miningModel, RegressionModel.NormalizationMethod.EXP, schema); } }
case "reg:gamma": case "reg:tweedie": this.obj = new GeneralizedLinearRegression(); break; case "count:poisson":
case "reg:gamma": case "reg:tweedie": this.obj = new GeneralizedLinearRegression(); break; case "count:poisson":
@Override public MiningModel encodeMiningModel(List<RegTree> regTrees, float base_score, Integer ntreeLimit, Schema schema){ Schema segmentSchema = schema.toAnonymousSchema(); MiningModel miningModel = createMiningModel(regTrees, base_score, ntreeLimit, segmentSchema) .setOutput(ModelUtil.createPredictedOutput(FieldName.create("xgbValue"), OpType.CONTINUOUS, DataType.FLOAT)); return MiningModelUtil.createRegression(miningModel, RegressionModel.NormalizationMethod.EXP, schema); } }