Forester is a rust crate for implementing various flavors of random forests and decision trees.
This workspace contains the forester library and examples in
separate crates.
Please refer to the subdirectories for more detailed documentation.
This example illustrates classification of three different labels.
The first image shows the decision regions created by a normal ExtraTreesClassifier.
Artifacts resulting from axis-aligned splits are clearly visible.
The second image demonstrates how a random forest can utilize an infinite-dimensional feature space to produce the effect of roted splits which adapt much nicer to the shape of the data.
A simple example demonstrating non-linear regression with the ExtraTreesRegressor.
