komodoml 0.0.0

A unified ML toolkit for models, metrics, plotting, and interpretability.

KomodoML

A unified ML toolkit for models, metrics, plotting, and interpretability.

Installation

Since KomodoML is not yet published on PyPI, you can install it directly from GitHub or set it up locally for development.

Install from GitHub

To install the latest version from the main branch:

pip install git+https://github.com/YerMarti/KomodoML.git

Local Development Installation

If you want to work on the library or run it in development mode:

git clone https://github.com/YerMarti/KomodoML.git
cd KomodoML
pip install -e .

Quick start

The following snippet trains a Decision Tree Classifier model using a k-fold resampling strategy.

from komodoml.models import DecisionTreeClf
from komodoml.resampling import KFoldFit

clf = DecisionTreeClf()
kfold = KFoldFit(k=5)
kfold.fit(clf, X, y)
print(kfold.scores_)

Alternatively, you can throw the resampling strategy into the model, whatever best suits you.

kfold = KFoldFit(k=5)
clf = DecisionTreeClf(resampling=kfold)
clf.fit(X, y)
print(kfold.scores_)

Documentation

• Documentation: https://yermarti.github.io/KomodoML/