/*
* 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 gKernelP = kernelP;
/**
* Stores all the configuration options for tree construction
* @param algo Learning goal. Supported:
* {@link Classification},
* {@link Regression}
* @param impurity Criterion used for information gain calculation.
* Supported for Classification: {@link Gini},
* {@link Entropy}.
* Supported for Regression: {@link Variance}.
* @param maxDepth Maximum depth of the tree.
* E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes.
* @param numClasses Number of classes for classification.
* (Ignored for regression.)
* Default value is 2 (binary classification).
* @param maxBins Maximum number of bins used for discretizing continuous features and
* for choosing how to split on features at each node.
* More bins give higher granularity.
* @param quantileCalculationStrategy Algorithm for calculating quantiles. Supported:
* {@link Sort}
* @param categoricalFeaturesInfo A map storing information about the categorical variables and the
* number of discrete values they take. For example, an entry (n ->
* k) implies the feature n is categorical with k categories 0,
* 1, 2, ... , k-1. It's important to note that features are
* zero-indexed.
* @param minInstancesPerNode Minimum number of instances each child must have after split.
* Default value is 1. If a split cause left or right child
* to have less than minInstancesPerNode,
* this split will not be considered as a valid split.
* @param minInfoGain Minimum information gain a split must get. Default value is 0.0.
* If a split has less information gain than minInfoGain,
* this split will not be considered as a valid split.
* @param maxMemoryInMB Maximum memory in MB allocated to histogram aggregation. Default value is
* 256 MB.
* @param subsamplingRate Fraction of the training data used for learning decision tree.
* @param useNodeIdCache If this is true, instead of passing trees to executors, the algorithm will
* maintain a separate RDD of node Id cache for each row.
* @param checkpointInterval How often to checkpoint when the node Id cache gets updated.
* E.g. 10 means that the cache will get checkpointed every 10 updates. If
* the checkpoint directory is not set in
* {@link SparkContext}, this setting is ignored.
* @classdesc
*/
/**
* @param {Algo} algo
* @param {Impurity} impurity
* @param {number} maxDepth
* @param {number} numClasses
* @param {number} maxBins
* @param {QuantileStrategy} quantileCalculationStrategy
* @param {Map} categoricalFeaturesInfo
* @param {number} minInstancesPerNode
* @param {number} minInfoGain
* @param {number} maxMemoryInMB
* @param {number} subsamplingRate
* @param {boolean} useNodeIdCache
* @param {number} checkpointInterval
* @class
* @memberof module:eclairjs/mllib/tree/configuration
*/
function Strategy() {
Utils.handleConstructor(this, arguments, gKernelP);
}
/**
*
* @param {integer} num
* @returns {Promise.<void>}
*/
Strategy.prototype.setNumClasses = function(num) {
var args = {
target: this,
method: 'setNumClasses',
args: Utils.wrapArguments(arguments)
};
return Utils.generate(args);
};
/**
*
* @param {integer} num
* @returns {Promise.<void>}
*/
Strategy.prototype.setMaxDepth = function(num) {
var args = {
target: this,
method: 'setMaxDepth',
args: Utils.wrapArguments(arguments)
};
return Utils.generate(args);
};
/**
* Sets categoricalFeaturesInfo using a Java Map.
* @param {Map} categoricalFeaturesInfo
* @returns {Promise.<Void>} A Promise that resolves to nothing.
*/
Strategy.prototype.setCategoricalFeaturesInfo = function(categoricalFeaturesInfo) {
var args = {
target: this,
method: 'setCategoricalFeaturesInfo',
args: [{value: categoricalFeaturesInfo, type: 'map'}]
};
return Utils.generate(args);
};
Strategy.moduleLocation = '/mllib/tree/configuration/Strategy';
return Strategy;
})();
};