Popular GitHub Repositories for Quantile Regression

A library for ready-made reinforcement learning agents and reusable components for neat prototyping

? Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

VAE + Quantile Networks for MNIST

Regularization Paths for Huber Loss Regression and Quantile Regression Penalized by Lasso or Elastic-Net

We carried out thematic clustering and differential prediction of number of retweets with Gradient Boosting and Quantile regression. We also performed text embedding with Bidirectional Encoder Representations (BERT, Google) for deep prediction with TensorFlow

This repository features an app that uses LightGBM machine learning to instantly evaluate real estate properties in Florianópolis, Brazil based on location, size, and other features, as well as proximity to risk areas, transportation, hospitals, markets, and green spaces. It also includes code and datasets for reproducing the analysis.