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hzlinyanggang
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predicting code
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‎.gitignore‎

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*.class
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.classpath
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.project
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/.settings/
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# Mobile Tools for Java (J2ME)
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.mtj.tmp/
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# virtual machine crash logs, see http://www.java.com/en/download/help/error_hotspot.xml
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hs_err_pid*
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/target/

‎pom.xml‎

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<?xml version="1.0"?>
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<project
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"
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xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
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<modelVersion>4.0.0</modelVersion>
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<groupId>org.lightgbm.predict4j</groupId>
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<artifactId>lightgbm_predict4j</artifactId>
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<version>1.0</version>
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<packaging>jar</packaging>
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<name>lightgbm_predict4j</name>
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<url>http://maven.apache.org</url>
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<dependencies>
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<dependency>
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<groupId>commons-io</groupId>
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<artifactId>commons-io</artifactId>
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<version>2.4</version>
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</dependency>
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<!-- https://mvnrepository.com/artifact/org.slf4j/slf4j-api -->
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<dependency>
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<groupId>org.slf4j</groupId>
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<artifactId>slf4j-api</artifactId>
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<version>1.7.21</version>
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</dependency>
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<dependency>
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<groupId>org.slf4j</groupId>
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<artifactId>log4j-over-slf4j</artifactId>
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<version>1.7.7</version>
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</dependency>
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<dependency>
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<groupId>org.slf4j</groupId>
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<artifactId>log4j-over-slf4j</artifactId>
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<version>1.7.7</version>
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</dependency>
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<dependency>
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<groupId>ch.qos.logback</groupId>
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<artifactId>logback-core</artifactId>
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<version>1.1.2</version>
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</dependency>
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<dependency>
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<groupId>ch.qos.logback</groupId>
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<artifactId>logback-access</artifactId>
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<version>1.1.2</version>
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</dependency>
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<dependency>
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<groupId>ch.qos.logback</groupId>
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<artifactId>logback-classic</artifactId>
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<version>1.1.2</version>
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</dependency>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>
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<version>4.12</version>
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<scope>test</scope>
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</dependency>
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</dependencies>
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<build>
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<finalName>lightgbm_predict4j</finalName>
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<resources>
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<resource>
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<directory>src/main/resources</directory>
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</resource>
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</resources>
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<testResources>
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<testResource>
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<directory>src/test/resources</directory>
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</testResource>
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</testResources>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-compiler-plugin</artifactId>
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<configuration>
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<compilerVersion>1.7</compilerVersion>
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<source>1.7</source>
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<target>1.7</target>
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</configuration>
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</plugin>
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</plugins>
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</build>
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</project>

‎src/main/java/org/lightgbm/predict4j/Application.java‎

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package org.lightgbm.predict4j;
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import java.io.FileInputStream;
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import java.io.FileNotFoundException;
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import java.io.IOException;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import org.apache.commons.io.IOUtils;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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/**
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* @author lyg5623
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*/
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public class Application {
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private static final Logger logger = LoggerFactory.getLogger(Application.class);
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private OverallConfig config = new OverallConfig();
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public static void main(String[] args) throws FileNotFoundException, IOException {
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args = "config=cluster_test.conf".split("\\s+");
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String modelPath = "LightGBM_model.txt";
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Application app = new Application(args);
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String dataPath = "lightgbm_test.txt";
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String outputPath = "LightGBM_predict_result.txt";
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app.run(modelPath, dataPath, outputPath);
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}
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public Application(String[] argv) throws FileNotFoundException, IOException {
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loadParameters(argv);
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}
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private void loadParameters(String[] argv) throws FileNotFoundException, IOException {
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Map<String, String> params = new HashMap<String, String>();
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for (int i = 0; i < argv.length; ++i) {
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String[] tmp_strs = argv[i].split("=");
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if (tmp_strs.length == 2) {
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String key = tmp_strs[0].trim();
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String value = tmp_strs[1].trim();
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if (key.length() <= 0) {
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continue;
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}
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params.put(key, value);
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} else {
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logger.warn(String.format("Unknown parameter in command line: %s", argv[i]));
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}
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}
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// check for alias
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ParameterAlias.keyAliasTransform(params);
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// read parameters from config file
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if (params.containsKey("config_file")) {
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List<String> lines = IOUtils.readLines(new FileInputStream(params.get("config_file")));
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if (lines != null) {
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for (String line : lines) {
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line = line.trim();
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// remove str after "#"
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if (line.startsWith("#"))
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continue;
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if (line.length() == 0) {
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continue;
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}
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String[] tmp_strs = line.split("=");
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if (tmp_strs.length == 2) {
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String key = tmp_strs[0].trim();
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String value = tmp_strs[1].trim();
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if (key.length() <= 0) {
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continue;
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}
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// Command-line has higher priority
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if (!params.containsKey(key))
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params.put(key, value);
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} else {
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logger.warn("Unknown parameter in config file: " + line);
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}
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}
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}
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}
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// check for alias again
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ParameterAlias.keyAliasTransform(params);
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// load configs
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config.set(params);
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logger.info("Finished loading parameters");
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}
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private void run(String modelPath, String dataPath, String outputPath) throws FileNotFoundException, IOException {
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Boosting boosting = initPredict(modelPath);
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predict(dataPath, outputPath, boosting);
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}
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private Boosting initPredict(String modelPath) throws FileNotFoundException, IOException {
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Boosting boosting = Boosting.createBoosting(modelPath);
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logger.info("Finished initializing prediction");
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return boosting;
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}
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private void predict(String dataPath, String outputPath, Boosting boosting) throws IOException {
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boosting.setNumIterationForPred(config.getIoConfig().getNumIterationPredict());
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// create predictor
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Predictor predictor = new Predictor(boosting, config.getIoConfig().isPredictRawScore(),
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config.getIoConfig().isPredictLeafIndex());
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predictor.Predict(dataPath, outputPath);
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logger.info("Finished prediction");
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}
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}

‎src/main/java/org/lightgbm/predict4j/Boosting.java‎

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package org.lightgbm.predict4j;
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import java.io.FileInputStream;
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import java.io.FileNotFoundException;
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import java.io.IOException;
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import java.io.Serializable;
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import java.util.List;
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import org.apache.commons.io.IOUtils;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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/**
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* @author lyg5623
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*/
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public abstract class Boosting implements Serializable {
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private static final Logger logger = LoggerFactory.getLogger(Boosting.class);
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private static final long serialVersionUID = -661844499486913306L;
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public static Boosting createBoosting(String modelPath) throws FileNotFoundException, IOException {
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Boosting boosting = null;
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String type = getBoostingTypeFromModelFile(modelPath);
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if (type.equals("tree")) {
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boosting = new GBDT();
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} else {
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logger.error("unknow submodel type in model file " + modelPath);
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}
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loadFileToBoosting(boosting, modelPath);
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return boosting;
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}
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private static boolean loadFileToBoosting(Boosting boosting, String modelPath)
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throws FileNotFoundException, IOException {
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if (boosting != null) {
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StringBuilder sb = new StringBuilder();
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List<String> lines = IOUtils.readLines(new FileInputStream(modelPath));
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for (String line : lines) {
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sb.append(line).append("\n");
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}
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if (!boosting.loadModelFromString(sb.toString()))
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return false;
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}
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return true;
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}
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public abstract boolean loadModelFromString(String modelStr);
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private static String getBoostingTypeFromModelFile(String modelPath) throws FileNotFoundException, IOException {
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List<String> lines = IOUtils.readLines(new FileInputStream(modelPath));
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return lines.get(0);
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}
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public abstract void setNumIterationForPred(int numIteration);
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public abstract List<Integer> predictLeafIndex(SparseVector vector);
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public abstract List<Double> predictRaw(SparseVector vector);
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public abstract List<Double> predict(SparseVector vector);
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}

‎src/main/java/org/lightgbm/predict4j/Common.java‎

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package org.lightgbm.predict4j;
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import java.util.List;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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/**
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* @author lyg5623
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*/
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public class Common {
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private static final Logger logger = LoggerFactory.getLogger(Common.class);
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public static String findFromLines(String[] lines, String keyWord) {
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for (String line : lines) {
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if (line.contains(keyWord))
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return line;
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}
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return "";
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}
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public static String join(String[] strs, String delimiter) {
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if (strs == null || strs.length == 0) {
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return "";
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}
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StringBuilder strBuf = new StringBuilder();
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strBuf.append(strs[0]);
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for (int i = 1; i < strs.length; ++i) {
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strBuf.append(delimiter).append(strs[i]);
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}
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return strBuf.toString();
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}
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public static String join(List<Double> strs, String delimiter) {
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if (strs == null || strs.size() == 0) {
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return "";
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}
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StringBuilder strBuf = new StringBuilder();
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strBuf.append(strs.get(0));
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for (int i = 1; i < strs.size(); ++i) {
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strBuf.append(delimiter).append(strs.get(i));
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}
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return strBuf.toString();
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}
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public static String join(String[] strs, int start, int end, String delimiter) {
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if (end - start <= 0) {
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return "";
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}
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start = Math.min(start, strs.length - 1);
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end = Math.min(end, strs.length);
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StringBuilder strBuf = new StringBuilder();
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strBuf.append(strs[start]);
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for (int i = start + 1; i < end; ++i) {
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strBuf.append(delimiter).append(strs[i]);
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}
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return strBuf.toString();
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}
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public static int[] stringToArrayInt(String str, String delimiter, int n) {
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String[] strs = str.split(delimiter);
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if (strs.length != n) {
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logger.error("StringToArray error, size doesn't match.");
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}
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int[] ret = new int[n];
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for (int i = 0; i < n; ++i) {
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ret[i] = Integer.parseInt(strs[i]);
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}
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return ret;
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}
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public static double[] stringToArrayDouble(String str, String delimiter, int n) {
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String[] strs = str.split(delimiter);
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if (strs.length != n) {
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logger.error("StringToArray error, size doesn't match.");
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}
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double[] ret = new double[n];
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for (int i = 0; i < n; ++i) {
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ret[i] = Double.parseDouble(strs[i]);
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}
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return ret;
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}
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/*
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* ! \brief Do inplace softmax transformaton on p_rec \param p_rec The input/output vector of the values.
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*/
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public static void softmax(double[] pRec) {
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double[] rec = pRec;
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double wmax = rec[0];
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for (int i = 1; i < rec.length; ++i) {
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wmax = Math.max(rec[i], wmax);
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}
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double wsum = 0.0f;
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for (int i = 0; i < rec.length; ++i) {
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rec[i] = Math.exp(rec[i] - wmax);
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wsum += rec[i];
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}
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for (int i = 0; i < rec.length; ++i) {
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rec[i] /= wsum;
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}
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}
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}

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