RF-PHATE
Project description
RF-PHATE
RF-PHATE provides code used in the paper, "Random Forest-based Diffusion Information Geometry for Supervised Visualization and Data Exploration" The code may be used to generate random forest proximities which may, in turn, be used in multiple dimensionality-reduction algorithms.
Installation
pip install rf_phate
Usage
from rf_phate import RandomForest, Embeddings
# Creates a random forest classifier object
rf = RandomForest.rf_classifier(n_estimators = 500, n_jobs = -2).fit(X, y)
# Generates random forest proximities based on the data matrix X
proximities = rf.get_proximities(X, method = 'oob', matrix_type = 'sparse')
# Generates the RF-PHATE embeddings
emb = Embeddings.get_rf_embeddings(proximities, label_type = 'classification', types = 'phate',
n_components = 2, random_state = 0, n_jobs = -2)
importance_correlation = Embeddings.get_importance_correlation(X, y, emb['phate'])
License
[GNU]
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