/*
* 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 JavaWrapper = require(EclairJS_Globals.NAMESPACE + '/JavaWrapper');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
/**
* :: Experimental ::
* Fit a parametric survival regression model named accelerated failure time (AFT) model
* ([[https://en.wikipedia.org/wiki/Accelerated_failure_time_model]])
* based on the Weibull distribution of the survival time.
* @classdesc
*
* @param {string} [uid] An immutable unique ID for the object and its derivatives.
* @class
* @memberof module:eclairjs/ml/regression
*/
var AFTSurvivalRegression = function (uid) {
this.logger = Logger.getLogger("ml/regression/AFTSurvivalRegression_js");
var jvmObject;
if (arguments.length > 0) {
if (arguments[0] instanceof org.apache.spark.ml.regression.AFTSurvivalRegression) {
jvmObject = arguments[0];
} else {
jvmObject = new org.apache.spark.ml.regression.AFTSurvivalRegression(uid);
}
} else {
jvmObject = new org.apache.spark.ml.regression.AFTSurvivalRegression();
}
JavaWrapper.call(this, jvmObject);
};
AFTSurvivalRegression.prototype = Object.create(JavaWrapper.prototype);
AFTSurvivalRegression.prototype.constructor = AFTSurvivalRegression;
/**
* @param {string} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setFeaturesCol = function (value) {
var javaObject = this.getJavaObject().setFeaturesCol(value);
return Utils.javaToJs(javaObject);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setLabelCol = function (value) {
var javaObject = this.getJavaObject().setLabelCol(value);
return Utils.javaToJs(javaObject);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setCensorCol = function (value) {
var javaObject = this.getJavaObject().setCensorCol(value);
return Utils.javaToJs(javaObject);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setPredictionCol = function (value) {
var javaObject = this.getJavaObject().setPredictionCol(value);
return Utils.javaToJs(javaObject);
};
/**
* @param {float[]} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setQuantileProbabilities = function (value) {
var javaObject = this.getJavaObject().setQuantileProbabilities(value);
return Utils.javaToJs(javaObject);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setQuantilesCol = function (value) {
var javaObject = this.getJavaObject().setQuantilesCol(value);
return Utils.javaToJs(javaObject);
};
/**
* Set if we should fit the intercept
* Default is true.
* @param {boolean} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setFitIntercept = function (value) {
var javaObject = this.getJavaObject().setFitIntercept(value);
return Utils.javaToJs(javaObject);
};
/**
* Set the maximum number of iterations.
* Default is 100.
* @param {integer} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setMaxIter = function (value) {
var javaObject = this.getJavaObject().setMaxIter(value);
return Utils.javaToJs(javaObject);
};
/**
* Set the convergence tolerance of iterations.
* Smaller value will lead to higher accuracy with the cost of more iterations.
* Default is 1E-6.
* @param {float} value
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.setTol = function (value) {
var javaObject = this.getJavaObject().setTol(value);
return Utils.javaToJs(javaObject);
};
/**
* @param {module:eclairjs/sql.Dataset} dataset
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
*/
AFTSurvivalRegression.prototype.fit = function (dataset) {
var dataset_uw = Utils.unwrapObject(dataset);
var javaObject = this.getJavaObject().fit(dataset_uw);
return Utils.javaToJs(javaObject);
};
/**
* @param {module:eclairjs/sql/types.StructType} schema
* @returns {module:eclairjs/sql/types.StructType}
*/
AFTSurvivalRegression.prototype.transformSchema = function (schema) {
var schema_uw = Utils.unwrapObject(schema);
var javaObject = this.getJavaObject().transformSchema(schema_uw);
return Utils.javaToJs(javaObject);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.prototype.copy = function (extra) {
var extra_uw = Utils.unwrapObject(extra);
var javaObject = this.getJavaObject().copy(extra_uw);
return Utils.javaToJs(javaObject);
};
/**
* An immutable unique ID for the object and its derivatives.
* @returns {string}
*/
AFTSurvivalRegression.prototype.uid = function () {
return this.getJavaObject().uid();
};
/**
* Param for censor column name. The value of this column could be 0 or 1.
* If the value is 1, it means the event has occurred i.e. uncensored; otherwise censored.
* @returns {module:eclairjs/ml/param.Param}
*/
AFTSurvivalRegression.prototype.censorCol = function () {
var javaObject = this.getJavaObject().censorCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
AFTSurvivalRegression.prototype.getCensorCol = function () {
return this.getJavaObject().getCensorCol();
};
/**
* Param for quantile probabilities array. Values of the quantile probabilities array should be in the range (0, 1) and the array should be non-empty.
* @returns {module:eclairjs/ml/param.DoubleArrayParam}
*/
AFTSurvivalRegression.prototype.quantileProbabilities = function () {
var javaObject = this.getJavaObject().quantileProbabilities();
return Utils.javaToJs(javaObject);
};
/**
* @returns {float[]}
*/
AFTSurvivalRegression.prototype.getQuantileProbabilities = function () {
return this.getJavaObject().getQuantileProbabilities();
};
/**
* Param for quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.
* @returns {module:eclairjs/ml/param.Param}
*/
AFTSurvivalRegression.prototype.quantilesCol = function () {
var javaObject = this.getJavaObject().quantilesCol();
return Utils.javaToJs(javaObject);
};
/**
* @returns {string}
*/
AFTSurvivalRegression.prototype.getQuantilesCol = function () {
return this.getJavaObject().getQuantilesCol();
};
/**
* Checks whether the input has quantiles column name.
* @returns {boolean}
*/
AFTSurvivalRegression.prototype.hasQuantilesCol = function () {
return this.getJavaObject().hasQuantilesCol();
};
/**
* Validates and transforms the input schema with the provided param map.
* @param {module:eclairjs/sql/types.StructType} schema input schema
* @param {boolean} fitting whether this is in fitting or prediction
* @returns {module:eclairjs/sql/types.StructType}
*/
AFTSurvivalRegression.prototype.validateAndTransformSchema = function (schema, fitting) {
var schema_uw = Utils.unwrapObject(schema);
var javaObject = this.getJavaObject().validateAndTransformSchema(schema_uw, fitting);
return Utils.javaToJs(javaObject);
};
//
// static methods
//
/**
* @param {string} path
* @returns {module:eclairjs/ml/regression.AFTSurvivalRegression}
*/
AFTSurvivalRegression.load = function (path) {
var javaObject = this.getJavaObject().load(path);
return Utils.javaToJs(javaObject);
};
module.exports = AFTSurvivalRegression;
})();