/*
* 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 Predictor = require(EclairJS_Globals.NAMESPACE + '/ml/Predictor');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
/**
* @classdesc
* Classifier trainer based on the Multilayer Perceptron.
* Each layer has sigmoid activation function, output layer has softmax.
* Number of inputs has to be equal to the size of feature vectors.
* Number of outputs has to be equal to the total number of labels.
* @class
* @extends module:eclairjs/ml.Predictor
* @memberof module:eclairjs/ml/classification
* @param {string} [uid]
*/
var MultilayerPerceptronClassifier = function (uid) {
this.logger = Logger.getLogger("ml_classification_MultilayerPerceptronClassifier_js");
var jvmObject;
if (uid) {
if (uid instanceof org.apache.spark.ml.classification.MultilayerPerceptronClassifier) {
jvmObject = uid;
} else {
jvmObject = new org.apache.spark.ml.classification.MultilayerPerceptronClassifier(uid);
}
} else {
jvmObject = new org.apache.spark.ml.classification.MultilayerPerceptronClassifier();
}
Predictor.call(this, jvmObject);
};
MultilayerPerceptronClassifier.prototype = Object.create(Predictor.prototype);
MultilayerPerceptronClassifier.prototype.constructor = MultilayerPerceptronClassifier;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {string}
*/
MultilayerPerceptronClassifier.prototype.uid = function () {
return this.getJavaObject().uid();
};
/**
* @param {integer[]} value
* @returns {module:eclairjs/ml/classification.MultilayerPerceptronClassifier}
*/
MultilayerPerceptronClassifier.prototype.setLayers = function (value) {
var javaObject = this.getJavaObject().setLayers(value);
return new MultilayerPerceptronClassifier(javaObject);
};
/**
* @param {integer} value
* @returns {module:eclairjs/ml/classification.MultilayerPerceptronClassifier}
*/
MultilayerPerceptronClassifier.prototype.setBlockSize = function (value) {
var javaObject = this.getJavaObject().setBlockSize(value);
return new MultilayerPerceptronClassifier(javaObject);
};
/**
* Set the maximum number of iterations.
* Default is 100.
* @param {integer} value
* @returns {module:eclairjs/ml/classification.MultilayerPerceptronClassifier}
*/
MultilayerPerceptronClassifier.prototype.setMaxIter = function (value) {
var javaObject = this.getJavaObject().setMaxIter(value);
return new MultilayerPerceptronClassifier(javaObject);
};
/**
* Set the convergence tolerance of iterations.
* Smaller value will lead to higher accuracy with the cost of more iterations.
* Default is 1E-4.
* @param {float} value
* @returns {module:eclairjs/ml/classification.MultilayerPerceptronClassifier}
*/
MultilayerPerceptronClassifier.prototype.setTol = function (value) {
var javaObject = this.getJavaObject().setTol(value);
return new MultilayerPerceptronClassifier(javaObject);
};
/**
* Set the seed for weights initialization.
* @param {integer} value
* @returns {module:eclairjs/ml/classification.MultilayerPerceptronClassifier}
*/
MultilayerPerceptronClassifier.prototype.setSeed = function (value) {
var javaObject = this.getJavaObject().setSeed(value);
return new MultilayerPerceptronClassifier(javaObject);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/classification.MultilayerPerceptronClassifier}
*/
MultilayerPerceptronClassifier.prototype.copy = function (extra) {
var extra_uw = Utils.unwrapObject(extra);
var javaObject = this.getJavaObject().copy(extra_uw);
return new MultilayerPerceptronClassifier(javaObject);
};
/**
* Layer sizes including input size and output size. Default: Array(1, 1)
* @returns {module:eclairjs/ml/param.IntArrayParam}
*/
MultilayerPerceptronClassifier.prototype.layers = function () {
var javaObject = this.getJavaObject().layers();
return Utils.javaToJs(javaObject);
};
/**
*
* @returns {integer[]}
*/
MultilayerPerceptronClassifier.prototype.getLayers = function () {
var javaObject = this.getJavaObject().getLayers();
return Utils.javaToJs(javaObject);
};
/**
* Block size for stacking input data in matrices to speed up the computation.
* Data is stacked within partitions. If block size is more than remaining data in
* a partition then it is adjusted to the size of this data. Recommended size is between 10 and 1000. Default: 128
* @returns {module:eclairjs/ml/param.IntArrayParam}
*/
MultilayerPerceptronClassifier.prototype.blockSize = function () {
var javaObject = this.getJavaObject().blockSize();
return Utils.javaToJs(javaObject);
};
/**
*
* @returns {integer}
*/
MultilayerPerceptronClassifier.prototype.getBlockSize = function () {
return this.getJavaObject().getBlockSize();
};
/**
* 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}
*/
MultilayerPerceptronClassifier.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 label column name.
* @returns {module:eclairjs/ml/param.Param}
*/
MultilayerPerceptronClassifier.prototype.labelCol = function () {
var javaObject = this.getJavaObject().labelCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
MultilayerPerceptronClassifier.prototype.getLabelCol = function () {
return this.getJavaObject().getLabelCol();
};
/**
* Param for features column name.
* @returns {module:eclairjs/ml/param.Param}
*/
MultilayerPerceptronClassifier.prototype.featuresCol = function () {
var javaObject = this.getJavaObject().featuresCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
MultilayerPerceptronClassifier.prototype.getFeaturesCol = function () {
return this.getJavaObject().getFeaturesCol();
};
/**
* Param for prediction column name.
* @returns {module:eclairjs/ml/param.Param}
*/
MultilayerPerceptronClassifier.prototype.predictionCol = function () {
var javaObject = this.getJavaObject().predictionCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
MultilayerPerceptronClassifier.prototype.getPredictionCol = function () {
return this.getJavaObject().getPredictionCol();
};
module.exports = MultilayerPerceptronClassifier;
})();