Java tutorial
/* Copyright (c) 2014 by Contributors 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 org.dmlc.xgboost4j; import java.io.IOException; import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.dmlc.xgboost4j.util.ErrorHandle; import org.dmlc.xgboost4j.util.XGBoostError; import org.dmlc.xgboost4j.util.Initializer; import org.dmlc.xgboost4j.wrapper.XgboostJNI; /** * DMatrix for xgboost, similar to the python wrapper xgboost.py * @author hzx */ public class DMatrix { private static final Log logger = LogFactory.getLog(DMatrix.class); long handle = 0; //load native library static { try { Initializer.InitXgboost(); } catch (IOException ex) { logger.error("load native library failed."); logger.error(ex); } } /** * sparse matrix type (CSR or CSC) */ public static enum SparseType { CSR, CSC; } /** * init DMatrix from file (svmlight format) * @param dataPath * @throws org.dmlc.xgboost4j.util.XGBoostError */ public DMatrix(String dataPath) throws XGBoostError { if (dataPath == null) { throw new NullPointerException("dataPath: null"); } long[] out = new long[1]; ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromFile(dataPath, 1, out)); handle = out[0]; } /** * create DMatrix from sparse matrix * @param headers index to headers (rowHeaders for CSR or colHeaders for CSC) * @param indices Indices (colIndexs for CSR or rowIndexs for CSC) * @param data non zero values (sequence by row for CSR or by col for CSC) * @param st sparse matrix type (CSR or CSC) * @throws org.dmlc.xgboost4j.util.XGBoostError */ public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XGBoostError { long[] out = new long[1]; if (st == SparseType.CSR) { ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSR(headers, indices, data, out)); } else if (st == SparseType.CSC) { ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSC(headers, indices, data, out)); } else { throw new UnknownError("unknow sparsetype"); } handle = out[0]; } /** * create DMatrix from dense matrix * @param data data values * @param nrow number of rows * @param ncol number of columns * @throws org.dmlc.xgboost4j.util.XGBoostError */ public DMatrix(float[] data, int nrow, int ncol) throws XGBoostError { long[] out = new long[1]; ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromMat(data, nrow, ncol, 0.0f, out)); handle = out[0]; } /** * used for DMatrix slice * @param handle */ private DMatrix(long handle) { this.handle = handle; } /** * set label of dmatrix * @param labels */ public void setLabel(float[] labels) throws XGBoostError { ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "label", labels)); } /** * set weight of each instance * @param weights * @throws org.dmlc.xgboost4j.util.XGBoostError */ public void setWeight(float[] weights) throws XGBoostError { ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "weight", weights)); } /** * if specified, xgboost will start from this init margin * can be used to specify initial prediction to boost from * @param baseMargin * @throws org.dmlc.xgboost4j.util.XGBoostError */ public void setBaseMargin(float[] baseMargin) throws XGBoostError { ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "base_margin", baseMargin)); } /** * if specified, xgboost will start from this init margin * can be used to specify initial prediction to boost from * @param baseMargin * @throws org.dmlc.xgboost4j.util.XGBoostError */ public void setBaseMargin(float[][] baseMargin) throws XGBoostError { float[] flattenMargin = flatten(baseMargin); setBaseMargin(flattenMargin); } /** * Set group sizes of DMatrix (used for ranking) * @param group * @throws org.dmlc.xgboost4j.util.XGBoostError */ public void setGroup(int[] group) throws XGBoostError { ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetGroup(handle, group)); } private float[] getFloatInfo(String field) throws XGBoostError { float[][] infos = new float[1][]; ErrorHandle.checkCall(XgboostJNI.XGDMatrixGetFloatInfo(handle, field, infos)); return infos[0]; } private int[] getIntInfo(String field) throws XGBoostError { int[][] infos = new int[1][]; ErrorHandle.checkCall(XgboostJNI.XGDMatrixGetUIntInfo(handle, field, infos)); return infos[0]; } /** * get label values * @return label * @throws org.dmlc.xgboost4j.util.XGBoostError */ public float[] getLabel() throws XGBoostError { return getFloatInfo("label"); } /** * get weight of the DMatrix * @return weights * @throws org.dmlc.xgboost4j.util.XGBoostError */ public float[] getWeight() throws XGBoostError { return getFloatInfo("weight"); } /** * get base margin of the DMatrix * @return base margin * @throws org.dmlc.xgboost4j.util.XGBoostError */ public float[] getBaseMargin() throws XGBoostError { return getFloatInfo("base_margin"); } /** * Slice the DMatrix and return a new DMatrix that only contains `rowIndex`. * @param rowIndex * @return sliced new DMatrix * @throws org.dmlc.xgboost4j.util.XGBoostError */ public DMatrix slice(int[] rowIndex) throws XGBoostError { long[] out = new long[1]; ErrorHandle.checkCall(XgboostJNI.XGDMatrixSliceDMatrix(handle, rowIndex, out)); long sHandle = out[0]; DMatrix sMatrix = new DMatrix(sHandle); return sMatrix; } /** * get the row number of DMatrix * @return number of rows * @throws org.dmlc.xgboost4j.util.XGBoostError */ public long rowNum() throws XGBoostError { long[] rowNum = new long[1]; ErrorHandle.checkCall(XgboostJNI.XGDMatrixNumRow(handle, rowNum)); return rowNum[0]; } /** * save DMatrix to filePath * @param filePath */ public void saveBinary(String filePath) { XgboostJNI.XGDMatrixSaveBinary(handle, filePath, 1); } public long getHandle() { return handle; } /** * flatten a mat to array * @param mat * @return */ private static float[] flatten(float[][] mat) { int size = 0; for (float[] array : mat) size += array.length; float[] result = new float[size]; int pos = 0; for (float[] ar : mat) { System.arraycopy(ar, 0, result, pos, ar.length); pos += ar.length; } return result; } @Override protected void finalize() { delete(); } public synchronized void delete() { if (handle != 0) { XgboostJNI.XGDMatrixFree(handle); handle = 0; } } }