hughstime

ML-NLP

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

awesome-interpretable-machine-learning

hughyw

new here

lofo-importance

Leave One Feature Out Importance

Feature-Selection-for-Machine-Learning

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

random-forest-importances

Code to compute permutation and drop-column importances in Python scikit-learn random forests

PDPbox

python partial dependence plot toolbox

Feature-Selection

Features selector based on the self selected-algorithm, loss function and validation method

unbiased-feature-importance

Implementation of unbiased measurement of feature importance in Random Forests

RandomForest-feature-importance

Explore Importance of Features in Random Forests

hpelm

High performance implementation of Extreme Learning Machines (fast randomized neural networks).

interpreting-decision-trees-and-random-forests

Unwrapping decision trees and random forests to make them less of a black box