/*
* 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 PipelineStage = require('../PipelineStage.js')();
var gKernelP = kernelP;
/**
* @classdesc
* Model fitted by {@link VectorIndexer}. Transform categorical features to use 0-based indices
* instead of their original values.
* - Categorical features are mapped to indices.
* - Continuous features (columns) are left unchanged.
* This also appends metadata to the output column, marking features as Numeric (continuous),
* Nominal (categorical), or Binary (either continuous or categorical).
* Non-ML metadata is not carried over from the input to the output column.
*
* This maintains vector sparsity.
*
* @param numFeatures Number of features, i.e., length of Vectors which this transforms
* @param categoryMaps Feature value index. Keys are categorical feature indices (column indices).
* Values are maps from original features values to 0-based category indices.
* If a feature is not in this map, it is treated as continuous.
* @class
* @memberof module:eclairjs/ml/feature
* @extends module:eclairjs/ml.PipelineStage
*/
function VectorIndexerModel() {
Utils.handleConstructor(this, arguments, gKernelP);
}
VectorIndexerModel.prototype = Object.create(PipelineStage.prototype);
VectorIndexerModel.prototype.constructor = VectorIndexerModel;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {Promise.<string>}
*/
VectorIndexerModel.prototype.uid = function () {
var args = {
target: this,
method: 'uid',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* @returns {Promise.<integer>}
*/
VectorIndexerModel.prototype.numFeatures = function () {
var args = {
target: this,
method: 'numFeatures',
args: Utils.wrapArguments(arguments),
returnType: Number
};
return Utils.generate(args);
};
/**
* @returns {Promise.<object>} Map object<integer,object<float,integer>>
*/
VectorIndexerModel.prototype.categoryMaps = function () {
var args = {
target: this,
method: 'categoryMaps',
args: Utils.wrapArguments(arguments),
stringify: true,
returnType: Object
};
return Utils.generate(args);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/feature.VectorIndexerModel}
*/
VectorIndexerModel.prototype.setInputCol = function(value) {
var args = {
target: this,
method: 'setInputCol',
args: Utils.wrapArguments(arguments),
returnType: VectorIndexerModel
};
return Utils.generate(args);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/feature.VectorIndexerModel}
*/
VectorIndexerModel.prototype.setOutputCol = function(value) {
var args = {
target: this,
method: 'setOutputCol',
args: Utils.wrapArguments(arguments),
returnType: VectorIndexerModel
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/sql.Dataset} dataset
* @returns {module:eclairjs/sql.Dataset}
*/
VectorIndexerModel.prototype.transform = function(dataset) {
var Dataset = require('../../sql/Dataset.js');
var args = {
target: this,
method: 'transform',
args: Utils.wrapArguments(arguments),
returnType: Dataset
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/sql/types.StructType} schema
* @returns {module:eclairjs/sql/types.StructType}
*/
VectorIndexerModel.prototype.transformSchema = function(schema) {
var StructType = require('../../sql/types/StructType.js')();
var args = {
target: this,
method: 'transformSchema',
args: Utils.wrapArguments(arguments),
returnType: StructType
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/feature.VectorIndexerModel}
*/
VectorIndexerModel.prototype.copy = function(extra) {
var args = {
target: this,
method: 'copy',
args: Utils.wrapArguments(arguments),
returnType: VectorIndexerModel
};
return Utils.generate(args);
};
/**
* @returns {MLWriter}
*/
VectorIndexerModel.prototype.write = function() {
throw "not implemented by ElairJS";
// var args ={
// target: this,
// method: 'write',
// returnType: MLWriter
//
// };
//
// return Utils.generate(args);
};
//
// static methods
//
/**
* @returns {MLReader}
*/
VectorIndexerModel.read = function() {
throw "not implemented by ElairJS";
// var args ={
// target: VectorIndexerModel,
// method: 'read',
// returnType: MLReader
//
// };
//
// return Utils.generate(args);
};
/**
* @param {string} path
* @returns {module:eclairjs/ml/feature.VectorIndexerModel}
*/
VectorIndexerModel.load = function(path) {
var args = {
target: VectorIndexerModel,
method: 'load',
kernelP: gKernelP,
static: true,
args: Utils.wrapArguments(arguments),
returnType: VectorIndexerModel
};
return Utils.generate(args);
};
VectorIndexerModel.moduleLocation = '/ml/feature/VectorIndexerModel';
return VectorIndexerModel;
})();
};