| Name | Version | Summary | date |
| HROCH |
1.4.12 |
Symbolic regression and classification |
2024-08-31 16:12:23 |
| ml2json |
0.4.0 |
A safe, transparent way to share and deploy scikit-learn models. |
2024-06-08 22:37:37 |
| sklearn-ml |
2.2 |
A light package build on scikit-learn, which is used for machine learning missions.By using it, you could conveniently train and use models at the same time, and do some model comparison. |
2024-04-25 14:40:23 |
| sagify |
0.25.4 |
Machine Learning Training, Tuning and Deployment on AWS |
2024-03-10 12:33:03 |
| scikit-transformers |
0.3.1 |
scikit-transformers is a very usefull package to enable and provide custom transformers such as LogColumnTransformer, BoolColumnTransformers and others fancy transformers. |
2024-02-09 23:42:52 |
| sumire |
1.0.2 |
Scikit-learn compatible Japanese text vectorizer for CPU-based Japanese natural language processing. |
2024-01-31 14:38:04 |
| adaptivebridge |
1.1.0 |
Revolutionizing ML adaptive modelling for handling missing features and data. The model can predict missing data in real-world scenarios. |
2024-01-29 13:21:58 |
| pwlreg |
1.0.1 |
A scikit-learn-compatible implementation of Piecewise Linear Regression |
2023-12-26 23:01:56 |
| pyhim |
0.9.1 |
Pipeline and functions to analyse multiplexed DNA-FISH data |
2023-12-13 13:26:49 |
| funpredict |
0.0.6 |
Introducing Fun Predict, the ultimate time-saver for machine learning! No more complex coding or tedious parameter tuning - just sit back and let Fun Predict build your basic models with ease. It's like having a personal assistant for your machine learning projects, making the process simple, efficient, and, well, Fun! 🛋 |
2023-11-12 08:55:15 |
| hypertune |
1.1.0 |
A library for performing hyperparameter optimization with Polyaxon. |
2023-11-02 08:58:15 |
| pmdarima |
2.0.4 |
Python's forecast::auto.arima equivalent |
2023-10-23 13:55:11 |
| scikit-datasets |
0.2.4 |
Scikit-learn-compatible datasets |
2023-08-08 14:02:18 |
| sklearn-nature-inspired-algorithms |
0.12.0 |
Search using nature inspired algorithms over specified parameter values for an sklearn estimator. |
2023-08-05 18:50:42 |
| pyaf |
5.0 |
Python Automatic Forecasting |
2023-07-12 22:24:01 |
| sktree |
0.1.3 |
Modern decision trees in Python |
2023-07-05 23:35:30 |
| lazyforecast |
0.0.1 |
LazyForecast is a Python library for performing univariate time series analysis using a lazy forecasting approach. This approach is designed to provide quick and simple forecasting models without requiring extensive configuration or parameter tuning. |
2023-06-27 10:10:26 |
| skbase |
0.4.6 |
Base classes for sklearn-like parametric objects |
2023-06-17 20:17:58 |
| example-wise-f1-maximizer |
0.1.5 |
A scikit-learn meta-estimator for multi-label classification that aims to maximize the example-wise F1 measure |
2023-06-16 11:15:57 |
| scikit-MDR |
0.4.5 |
Multifactor Dimensionality Reduction (MDR) |
2023-06-14 17:45:02 |