[jvm-packages] support specified feature names when getModelDump and getFeatureScore (#3733)
* [jvm-packages] support specified feature names for jvm when get ModelDump and get FeatureScore (#3725) * typo and style fix
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zengxy
Nan Zhu
parent
34522d56f0
commit
9e73087324
@ -369,15 +369,68 @@ public class Booster implements Serializable, KryoSerializable {
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return modelInfos[0];
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}
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/**
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* Get the dump of the model as a string array with specified feature names.
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*
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* @param featureNames Names of the features.
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* @return dumped model information
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* @throws XGBoostError
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*/
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public String[] getModelDump(String[] featureNames, boolean withStats) throws XGBoostError {
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return getModelDump(featureNames, withStats, "text");
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}
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public String[] getModelDump(String[] featureNames, boolean withStats, String format)
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throws XGBoostError {
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int statsFlag = 0;
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if (withStats) {
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statsFlag = 1;
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}
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if (format == null) {
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format = "text";
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}
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String[][] modelInfos = new String[1][];
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XGBoostJNI.checkCall(XGBoostJNI.XGBoosterDumpModelExWithFeatures(
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handle, featureNames, statsFlag, format, modelInfos));
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return modelInfos[0];
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}
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/**
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* Get importance of each feature with specified feature names.
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*
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* @return featureScoreMap key: feature name, value: feature importance score, can be nill.
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* @throws XGBoostError native error
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*/
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public Map<String, Integer> getFeatureScore(String[] featureNames) throws XGBoostError {
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String[] modelInfos = getModelDump(featureNames, false);
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Map<String, Integer> featureScore = new HashMap<>();
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for (String tree : modelInfos) {
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for (String node : tree.split("\n")) {
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String[] array = node.split("\\[");
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if (array.length == 1) {
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continue;
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}
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String fid = array[1].split("\\]")[0];
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fid = fid.split("<")[0];
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if (featureScore.containsKey(fid)) {
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featureScore.put(fid, 1 + featureScore.get(fid));
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} else {
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featureScore.put(fid, 1);
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}
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}
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}
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return featureScore;
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}
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/**
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* Get importance of each feature
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*
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* @return featureMap key: feature index, value: feature importance score, can be nill
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* @return featureScoreMap key: feature index, value: feature importance score, can be nill
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* @throws XGBoostError native error
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*/
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public Map<String, Integer> getFeatureScore(String featureMap) throws XGBoostError {
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String[] modelInfos = getModelDump(featureMap, false);
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Map<String, Integer> featureScore = new HashMap<String, Integer>();
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Map<String, Integer> featureScore = new HashMap<>();
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for (String tree : modelInfos) {
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for (String node : tree.split("\n")) {
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String[] array = node.split("\\[");
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@ -111,6 +111,9 @@ class XGBoostJNI {
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public final static native int XGBoosterDumpModelEx(long handle, String fmap, int with_stats,
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String format, String[][] out_strings);
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public final static native int XGBoosterDumpModelExWithFeatures(
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long handle, String[] feature_names, int with_stats, String format, String[][] out_strings);
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public final static native int XGBoosterGetAttr(long handle, String key, String[] out_string);
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public final static native int XGBoosterSetAttr(long handle, String key, String value);
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public final static native int XGBoosterLoadRabitCheckpoint(long handle, int[] out_version);
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@ -187,16 +187,42 @@ class Booster private[xgboost4j](private[xgboost4j] var booster: JBooster)
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booster.getModelDump(featureMap, withStats, format)
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}
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/**
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* Dump model as Array of string with specified feature names.
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*
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* @param featureNames Names of features.
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*/
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@throws(classOf[XGBoostError])
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def getModelDump(featureNames: Array[String]): Array[String] = {
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booster.getModelDump(featureNames, false, "text")
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}
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def getModelDump(featureNames: Array[String], withStats: Boolean, format: String)
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: Array[String] = {
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booster.getModelDump(featureNames, withStats, format)
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}
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/**
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* Get importance of each feature
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*
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* @return featureMap key: feature index, value: feature importance score
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* @return featureScoreMap key: feature index, value: feature importance score
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*/
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@throws(classOf[XGBoostError])
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def getFeatureScore(featureMap: String = null): mutable.Map[String, Integer] = {
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booster.getFeatureScore(featureMap).asScala
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}
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/**
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* Get importance of each feature with specified feature names.
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*
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* @return featureScoreMap key: feature name, value: feature importance score
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*/
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@throws(classOf[XGBoostError])
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def getFeatureScore(featureNames: Array[String]): mutable.Map[String, Integer] = {
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booster.getFeatureScore(featureNames).asScala
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}
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def getVersion: Int = booster.getVersion
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def toByteArray: Array[Byte] = {
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@ -656,6 +656,56 @@ JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterDumpModel
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return ret;
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}
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/*
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* Class: ml_dmlc_xgboost4j_java_XGBoostJNI
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* Method: XGBoosterDumpModelExWithFeatures
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* Signature: (JLjava/lang/String;I[[Ljava/lang/String;)I
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*/
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JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterDumpModelExWithFeatures
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(JNIEnv *jenv, jclass jcls, jlong jhandle, jobjectArray jfeature_names, jint jwith_stats,
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jstring jformat, jobjectArray jout) {
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BoosterHandle handle = (BoosterHandle) jhandle;
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bst_ulong feature_num = (bst_ulong)jenv->GetArrayLength(jfeature_names);
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std::vector<std::string> feature_names;
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std::vector<char*> feature_names_char;
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std::string feature_type_q = "q";
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std::vector<char*> feature_types_char;
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for (bst_ulong i = 0; i < feature_num; ++i) {
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jstring jfeature_name = (jstring)jenv->GetObjectArrayElement(jfeature_names, i);
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const char *s = jenv->GetStringUTFChars(jfeature_name, 0);
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feature_names.push_back(std::string(s, jenv->GetStringLength(jfeature_name)));
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if (s != nullptr) jenv->ReleaseStringUTFChars(jfeature_name, s);
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if (feature_names.back().length() == 0) feature_names.pop_back();
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}
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for (size_t i = 0; i < feature_names.size(); ++i) {
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feature_names_char.push_back(&feature_names[i][0]);
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feature_types_char.push_back(&feature_type_q[0]);
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}
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const char *format = jenv->GetStringUTFChars(jformat, 0);
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bst_ulong len = 0;
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char **result;
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int ret = XGBoosterDumpModelExWithFeatures(handle, feature_num,
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(const char **) dmlc::BeginPtr(feature_names_char),
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(const char **) dmlc::BeginPtr(feature_types_char),
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jwith_stats, format, &len, (const char ***) &result);
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jsize jlen = (jsize) len;
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jobjectArray jinfos = jenv->NewObjectArray(jlen, jenv->FindClass("java/lang/String"), jenv->NewStringUTF(""));
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for(int i=0 ; i<jlen; i++) {
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jenv->SetObjectArrayElement(jinfos, i, jenv->NewStringUTF((const char*) result[i]));
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}
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jenv->SetObjectArrayElement(jout, 0, jinfos);
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return ret;
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}
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/*
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* Class: ml_dmlc_xgboost4j_java_XGBoostJNI
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* Method: XGBoosterLoadRabitCheckpoint
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@ -223,6 +223,14 @@ JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterGetModelR
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JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterDumpModelEx
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(JNIEnv *, jclass, jlong, jstring, jint, jstring, jobjectArray);
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/*
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* Class: ml_dmlc_xgboost4j_java_XGBoostJNI
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* Method: XGBoosterDumpModelExWithFeatures
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* Signature: (JLjava/lang/String;I[[Ljava/lang/String;)I
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*/
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JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterDumpModelExWithFeatures
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(JNIEnv *, jclass, jlong, jobjectArray, jint, jstring, jobjectArray);
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/*
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* Class: ml_dmlc_xgboost4j_java_XGBoostJNI
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* Method: XGBoosterGetAttr
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@ -271,6 +271,24 @@ public class BoosterImplTest {
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Booster booster = trainBooster(trainMat, testMat);
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String[] dump = booster.getModelDump("", false, "json");
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TestCase.assertEquals(" { \"nodeid\":", dump[0].substring(0, 13));
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// test with specified feature names
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String[] featureNames = new String[126];
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for(int i = 0; i < 126; i++) featureNames[i] = "test_feature_name_" + i;
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dump = booster.getModelDump(featureNames, false, "json");
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TestCase.assertTrue(dump[0].contains("test_feature_name_"));
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}
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@Test
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public void testGetFeatureImportance() throws XGBoostError {
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DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
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DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
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Booster booster = trainBooster(trainMat, testMat);
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String[] featureNames = new String[126];
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for(int i = 0; i < 126; i++) featureNames[i] = "test_feature_name_" + i;
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Map<String, Integer> scoreMap = booster.getFeatureScore(featureNames);
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for (String fName: scoreMap.keySet()) TestCase.assertTrue(fName.startsWith("test_feature_name_"));
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}
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@Test
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