/*
* 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.
*/
module.exports = function(kernelP) {
return (function() {
var Utils = require('../../utils.js');
var ProbabilisticClassificationModel = require('./ProbabilisticClassificationModel')();
var ParamMap = require('../../ml/param/ParamMap')();
var Param = require('../../ml/param/Param')();
var Vector = require('../../mllib/linalg/Vector');
var Matrix = require('../../mllib/linalg/Matrix');
var DoubleParam = require('../param/DoubleParam')();
var StructType = require('../../sql/types/StructType')();
var gKernelP = kernelP;
/**
* @classdesc
* Model produced by {@link module:eclairjs/ml/classification.NaiveBayes}
* @class
* @memberof module:eclairjs/ml/classification
* @extends module:eclairjs/ml/classification.ProbabilisticClassificationModel
*/
function NaiveBayesModel() {
Utils.handleConstructor(this, arguments, gKernelP);
}
NaiveBayesModel.prototype = Object.create(ProbabilisticClassificationModel.prototype);
NaiveBayesModel.prototype.constructor = NaiveBayesModel;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {Promise.<string>}
*/
NaiveBayesModel.prototype.uid = function() {
var args = {
target: this,
method: 'uid',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
*
* @returns {module:eclairjs/mllib/linalg.Vector}
*/
NaiveBayesModel.prototype.pi = function() {
var args = {
target: this,
method: 'pi',
args: Utils.wrapArguments(arguments),
returnType: Vector
};
return Utils.generate(args);
};
/**
*
* @returns {module:eclairjs/mllib/linalg.Matrix}
*/
NaiveBayesModel.prototype.theta = function() {
var args = {
target: this,
method: 'theta',
args: Utils.wrapArguments(arguments),
returnType: Matrix
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/mllib/classification.NaiveBayesModel}
*/
NaiveBayesModel.prototype.copy = function(extra) {
var args = {
target: this,
method: 'copy',
args: Utils.wrapArguments(arguments),
returnType: NaiveBayesModel
};
return Utils.generate(args);
};
/**
* @returns {Promise.<string>}
*/
NaiveBayesModel.prototype.toString = function() {
var args = {
target: this,
method: 'toString',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* @returns {module:eclairjs/ml/util.MLWriter}
*/
NaiveBayesModel.prototype.write = function() {
throw "not implemented by ElairJS";
};
/**
* The smoothing parameter. (default = 1.0).
* @returns {module:eclairjs/ml/param.DoubleParam}
*/
NaiveBayesModel.prototype.smoothing = function() {
var args = {
target: this,
method: 'smoothing',
args: Utils.wrapArguments(arguments),
returnType: DoubleParam
};
return Utils.generate(args);
};
/**
*
* @returns {Promise.<Number>}
*/
NaiveBayesModel.prototype.getSmoothing = function() {
var args = {
target: this,
method: 'getSmoothing',
args: Utils.wrapArguments(arguments),
returnType: Number
};
return Utils.generate(args);
};
/**
* The model type which is a string (case-sensitive). Supported options: "multinomial" and "bernoulli". (default = multinomial)
* @returns {module:eclairjs/ml/param.Param}
*/
NaiveBayesModel.prototype.modelType = function() {
var args = {
target: this,
method: 'modelType',
args: Utils.wrapArguments(arguments),
returnType: Param
};
return Utils.generate(args);
};
/**
*
* @returns {Promise.<string>}
*/
NaiveBayesModel.prototype.getModelType = function() {
var args = {
target: this,
method: 'getModelType',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* 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}
*/
NaiveBayesModel.prototype.validateAndTransformSchema = function(schema, fitting, featuresDataType) {
var args = {
target: this,
method: 'validateAndTransformSchema',
args: Utils.wrapArguments(arguments),
returnType: StructType
};
return Utils.generate(args);
};
/**
* Param for raw prediction (a.k.a. confidence) column name.
* @returns {module:eclairjs/ml/param.Param}
*/
NaiveBayesModel.prototype.rawPredictionCol = function() {
var args = {
target: this,
method: 'rawPredictionCol',
args: Utils.wrapArguments(arguments),
returnType: Param
};
return Utils.generate(args);
};
/**
*
* @returns {Promise.<string>}
*/
NaiveBayesModel.prototype.getRawPredictionCol = function() {
var args = {
target: this,
method: 'getRawPredictionCol',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
//
// static methods
//
/**
* @returns {module:eclairjs/ml/util.MLReader}
*/
NaiveBayesModel.read = function() {
throw "not implemented by ElairJS";
};
/**
* @param {Promise.<string>} path
* @returns {module:eclairjs/mllib/classification.NaiveBayesModel}
*/
NaiveBayesModel.load = function(path) {
var args = {
target: NaiveBayesModel,
method: 'load',
kernelP: gKernelP,
static: true,
args: Utils.wrapArguments(arguments),
returnType: NaiveBayesModel
};
return Utils.generate(args)
};
NaiveBayesModel.moduleLocation = '/ml/classification/NaiveBayesModel';
return NaiveBayesModel;
})();
};