/*
* Copyright 2016 IBM Corp.
*
* 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.
*/
(function () {
var PipelineStage = require(EclairJS_Globals.NAMESPACE + '/ml/PipelineStage');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
/**
* @classdesc
* [Decision tree]{@link http://en.wikipedia.org/wiki/Decision_tree_learning} model for classification.
* It supports both binary and multiclass labels, as well as both continuous and categorical
* features.
* @class
* @memberof module:eclairjs/ml/classification
*/
var DecisionTreeClassificationModel = function(jvmObject) {
this.logger = Logger.getLogger("ml.classification.DecisionTreeClassificationModel_js");
PipelineStage.call(this, jvmObject);
};
DecisionTreeClassificationModel.prototype = Object.create(PipelineStage.prototype);
DecisionTreeClassificationModel.prototype.constructor = DecisionTreeClassificationModel;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.uid = function () {
return this.getJavaObject().uid();
};
/**
*
* @returns {module:eclairjs/ml/tree.Node}
*/
DecisionTreeClassificationModel.prototype.rootNode = function () {
return Utils.javaToJs(this.getJavaObject().rootNode());
};
/**
* Returns the number of features the model was trained on. If unknown, returns -1
* @returns {integer}
*/
DecisionTreeClassificationModel.prototype.numFeatures = function () {
return this.getJavaObject().numFeatures();
};
/**
* Number of classes (values which the label can take).
* @returns {integer}
*/
DecisionTreeClassificationModel.prototype.numClasses = function () {
return this.getJavaObject().numClasses();
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/classification.DecisionTreeClassificationModel}
*/
DecisionTreeClassificationModel.prototype.copy = function(extra) {
var extra_uw = Utils.unwrapObject(extra);
var javaObject = this.getJavaObject().copy(extra_uw);
return new DecisionTreeClassificationModel(javaObject);
};
/**
* Validates and transforms the input schema with the provided param map.
* @param {module:eclairjs/sql/types.StructType} schema
* @param {boolean} fitting whether this is in fitting
* @param {module:eclairjs/sql/types.DataType} featuresDataType SQL DataType for FeaturesType.
* E.g., {@link module:eclairjs/sql/types.VectorUDT}for vector features
* @returns {module:eclairjs/sql/types.StructType}
*/
DecisionTreeClassificationModel.prototype.validateAndTransformSchema = function (schema, fitting, featuresDataType) {
var schema_uw = Utils.unwrapObject(schema);
var featuresDataType_uw = Utils.unwrapObject(featuresDataType);
var javaObject = this.getJavaObject().validateAndTransformSchema(schema_uw, fitting, featuresDataType_uw);
return Utils.javaToJs(javaObject);
};
/**
* Param for raw prediction (a.k.a. confidence) column name.
* @returns {module:eclairjs/ml/param.Param}
*/
DecisionTreeClassificationModel.prototype.rawPredictionCol = function() {
var javaObject = this.getJavaObject().rawPredictionCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.getRawPredictionCol = function() {
return this.getJavaObject().getRawPredictionCol();
};
/**
* Param for label column name.
* @returns {module:eclairjs/ml/param.Param}
*/
DecisionTreeClassificationModel.prototype.labelCol = function() {
var javaObject = this.getJavaObject().labelCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.getLabelCol = function() {
return this.getJavaObject().getLabelCol();
};
/**
* Param for features column name.
* @returns {module:eclairjs/ml/param.Param}
*/
DecisionTreeClassificationModel.prototype.featuresCol = function() {
var javaObject = this.getJavaObject().featuresCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.getFeaturesCol = function() {
return this.getJavaObject().getFeaturesCol();
};
/**
* Param for prediction column name.
* @returns {module:eclairjs/ml/param.Param}
*/
DecisionTreeClassificationModel.prototype.predictionCol = function() {
var javaObject = this.getJavaObject().predictionCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.getPredictionCol = function() {
return this.getJavaObject().getPredictionCol();
};
/**
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.toString = function() {
return this.getJavaObject().toString();
};
/**
* @returns {string}
*/
DecisionTreeClassificationModel.prototype.toDebugString = function() {
return this.getJavaObject().toDebugString();
};
/**
* @returns {module:eclairjs/ml/util.MLWriter}
*/
DecisionTreeClassificationModel.prototype.write = function() {
var javaObject = this.getJavaObject().write();
return Utils.javaToJs(javaObject);
};
//
// static methods
//
/**
* @returns {module:eclairjs/ml/util.MLReader}
* @static
*/
DecisionTreeClassificationModel.read = function() {
var javaObject = org.apache.spark.ml.classification.DecisionTreeClassificationModel.read();
return Utils.javaToJs(javaObject);
};
/**
* @param {string} path
* @static
* @returns {module:eclairjs/ml/classification.DecisionTreeClassificationModel}
*/
DecisionTreeClassificationModel.load = function(path) {
var javaObject = org.apache.spark.ml.classification.DecisionTreeClassificationModel.load(path);
return new DecisionTreeClassificationModel(javaObject);
};
module.exports = DecisionTreeClassificationModel;
})();