Search Packages

arm-mango

Parallel Hyperparameter Tuning in Python

polyfit

Scikit learn compatible constrained and robust polynomial regression in Python

xaisuite

XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.

onehot

One-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly.

constrainedlr

Drop-in replacement of sklearn's Linear Regression with coefficients constraints

pyoperon

Python bindings and scikit-learn interface for the Operon library for symbolic regression.

panelsplit

A tool for performing cross-validation with panel data

pyadlml

Sklearn flavored library containing numerous Activity of Daily Livings datasets, preprocessing methods, visualizations and models.

sklearn-utilities

Utilities for scikit-learn. Append prediction to x, append prediction to x single, append x prediction to x, compose var estimator, data frame wrapper, drop by noise prediction, drop missing rows y, dummy regressor var, estimator wrapper base, excluded column transformer pandas, feature union pandas, id transformer, included column transformer pand

boost-loss

Utilities for easy use of custom losses in CatBoost, LightGBM, XGBoost.

lightgbm-callbacks

A collection of LightGBM callbacks. (DART early stopping, tqdm progress bar)

bleedml

Bleeding Edge machine learning algorithms

palladio

ParALleL frAmework for moDel selectIOn

scikit-stan

No description available

inne

A scikit-learn-compatible module for Isolation-based anomaly detection using nearest-neighbor ensembles

pipelinetweak

additional wrapper and classes for sklearn's pipeline API

datefeatures

Feature engineering sklearn transformer for dates

thermoencoder

Thermometer Encoding for ordinal variables

ecf

Empirical Christoffel function for anomaly detection

pctl-scale

Scale a variable into an open interval (0,1) whereas values within a given lower and upper percentile maintain a linear relation, and outlier saturate towards the interval limits.

optiml

Optimizers for/and sklearn compatible Machine Learning models