/* * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package com.facebook.presto.ml; import com.facebook.presto.ml.type.ModelType; import com.google.common.base.Throwables; import libsvm.svm; import libsvm.svm_model; import libsvm.svm_parameter; import java.io.BufferedReader; import java.io.ByteArrayInputStream; import java.io.IOException; import java.io.InputStreamReader; import static com.facebook.presto.ml.type.RegressorType.REGRESSOR; import static java.util.Objects.requireNonNull; public class SvmRegressor extends AbstractSvmModel implements Regressor { public SvmRegressor() { this(LibSvmUtils.parseParameters("")); } public SvmRegressor(svm_parameter params) { super(params); } private SvmRegressor(svm_model model) { super(model); } public static SvmRegressor deserialize(byte[] modelData) { // TODO do something with the hyperparameters try { svm_model model = svm.svm_load_model(new BufferedReader(new InputStreamReader(new ByteArrayInputStream(modelData)))); return new SvmRegressor(model); } catch (IOException e) { throw Throwables.propagate(e); } } @Override public double regress(FeatureVector features) { requireNonNull(model, "model is null"); return svm.svm_predict(model, toSvmNodes(features)); } @Override public ModelType getType() { return REGRESSOR; } @Override protected int getLibsvmType() { return svm_parameter.NU_SVR; } }