best_split,DecisionTreeClassifier-method

object

parms

<p>Function to get best split in Decision Tree.
Find the best split for node. "Beast" means that the mean
of impurity is the least possible.
To find the best division. Let's iterate through all the features.
All threshold / feature pairs will be computed in the numerical
features. In the features that are not numerical,
We get the best group of possible values
will be obtained based on an algorithm with the function
get_levels_categoric</p>

Providing a collection of techniques for semi-supervised
classification, regression and clustering. In semi-supervised problem, both labeled and unlabeled
data are used to train a classifier. The package includes a collection of
semi-supervised learning techniques: self-training, co-training, democratic,
decision tree, random forest, 'S3VM' ... etc, with a fairly intuitive interface
that is easy to use.

Francisco Jes<c3><ba>s Palomares Alabarce

SSLR

Semi-Supervised Classification, Regression and Clustering
Methods

Jos<c3><a9> Manuel Ben<c3><ad>tez

Isaac Triguero

Christoph Bergmeir

Mabel Gonz<c3><a1>lez

best_split,DecisionTreeClassifier-method function

Best Split function — best_split,DecisionTreeClassifier-method

Best Split function

best_split,DecisionTreeClassifier-method: Best Split function

Description

Usage

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Value