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DecisionTree:: (16 methods):
__construct()
train()
getColumnTypes()
getGiniIndex()
setNumFeatures()
setColumnNames()
getHtml()
getFeatureImportances()
getSplitLeaf()
getBestSplit()
getSelectedFeatures()
preprocess()
isCategoricalColumn()
setSelectedFeatures()
getSplitNodesByColumn()
predictSample()
Class: DecisionTree - X-Ref
__construct(int $maxDepth = 10) X-Ref |
train(array $samples, array $targets) X-Ref |
No description |
getColumnTypes(array $samples) X-Ref |
No description |
getGiniIndex($baseValue, array $colValues, array $targets) X-Ref |
param: mixed $baseValue |
setNumFeatures(int $numFeatures) X-Ref |
This method is used to set number of columns to be used when deciding a split at an internal node of the tree. <br> If the value is given 0, then all features are used (default behaviour), otherwise the given value will be used as a maximum for number of columns randomly selected for each split operation. return: $this |
setColumnNames(array $names) X-Ref |
A string array to represent columns. Useful when HTML output or column importances are desired to be inspected. return: $this |
getHtml() X-Ref |
No description |
getFeatureImportances() X-Ref |
This will return an array including an importance value for each column in the given dataset. The importance values are normalized and their total makes 1.<br/> |
getSplitLeaf(array $records, int $depth = 0) X-Ref |
No description |
getBestSplit(array $records) X-Ref |
No description |
getSelectedFeatures() X-Ref |
Returns available features/columns to the tree for the decision making process. <br> If a number is given with setNumFeatures() method, then a random selection of features up to this number is returned. <br> If some features are manually selected by use of setSelectedFeatures(), then only these features are returned <br> If any of above methods were not called beforehand, then all features are returned by default. |
preprocess(array $samples) X-Ref |
No description |
isCategoricalColumn(array $columnValues) X-Ref |
No description |
setSelectedFeatures(array $selectedFeatures) X-Ref |
Used to set predefined features to consider while deciding which column to use for a split |
getSplitNodesByColumn(int $column, DecisionTreeLeaf $node) X-Ref |
Collects and returns an array of internal nodes that use the given column as a split criterion |
predictSample(array $sample) X-Ref |
return: mixed |