Cubist
Rule-based regressor
A Python package implementing Quinlan's Cubist regression model for generating rule-based predictive models
A Python package for fitting Quinlan's Cubist regression model
44 stars
0 watching
3 forks
Language: C
last commit: 11 months ago data-sciencemachine-learningpythonregressionscikit-learn
Related projects:
| Repository | Description | Stars |
|---|---|---|
| | A JavaScript implementation of Partial Least Squares regression and related algorithms for exploratory data modeling | 10 |
| | A Python framework for Bayesian inference and regression using Gaussian processes. | 24 |
| | An implementation of a lightweight convolutional neural network architecture for mobile devices | 191 |
| | A structured learning and prediction library for Python | 664 |
| | An algorithm implementation for rule-based prediction using gradient boosting and L1 regularization. | 411 |
| | A MATLAB framework for ordinal regression and classification algorithms | 116 |
| | A linear regression library for building predictions in machine learning | 12 |
| | A lightweight wrapper around PyTorch to prevent CUDA out-of-memory errors and optimize model execution | 1,823 |
| | A unified framework for probabilistic regression and prediction with Python-based tools. | 250 |
| | A PyTorch implementation of the Squeezenet model with pre-trained weights on CIFAR 10 data for deep learning tasks. | 91 |
| | A tool that predicts pKa values of ionizable groups in proteins and protein-ligand complexes based on their 3D structure. | 274 |
| | Pytorch implementation of unsupervised depth and ego-motion learning from video sequences | 1,022 |
| | A Julia package for building and analyzing regression models using generalized linear models | 599 |
| | A collection of PyTorch implementations of various scene graph generation models | 732 |
| | A Python package for time series classification and analysis | 1,781 |