# `splitcriteria`

Module containing split criteria for decision trees.

Decision trees are built by splitting the data into groups based on a split
criterion. The split criterion is a function that measures the quality of a
split.

## Classes

| [`GiniSplitCriterion`](capymoa.core.moa.splitcriteria.GiniSplitCriterion.md#capymoa.core.moa.splitcriteria.GiniSplitCriterion)                           | Goodness of split using Gini impurity.                                         |
|-------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
| [`InfoGainSplitCriterion`](capymoa.core.moa.splitcriteria.InfoGainSplitCriterion.md#capymoa.core.moa.splitcriteria.InfoGainSplitCriterion)                   | Goodness of split using information gain.                                      |
| [`SplitCriterion`](capymoa.core.moa.splitcriteria.SplitCriterion.md#capymoa.core.moa.splitcriteria.SplitCriterion)                                   | Split criteria are used to evaluate the quality of a split in a decision tree. |
| [`VarianceReductionSplitCriterion`](capymoa.core.moa.splitcriteria.VarianceReductionSplitCriterion.md#capymoa.core.moa.splitcriteria.VarianceReductionSplitCriterion) | Goodness of split criterion based on variance reduction.                       |