mcs_kfold stands for "monte carlo stratified k fold". This library attempts to achieve equal distribution of discrete/categorical variables in all folds. The greatest advantage of this method is that it can be applied to multi-dimensional targets.

Fast Online Triplet mining in Pytorch

Predicts which telecom customers are likely to churn with 95% accuracy using real-world data features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.

Data sampling library

Python package for stratifying, sampling, and estimating model performance with fewer annotations.

This code assigns participants to an experimental group and ensures balanced physical attributes without knowing the participants in advance.

(77,86% R) Floresta Aleatória aprimorada para a previsão de aluguel.

Loan approval system using svm

A Python-based tool for simple and stratified sampling of *CREDITOS MI VIVIENDA* data, featuring a Tkinter GUI for easy data selection and visualization.

Data sampling library