-
ML-NLP Public
Forked from NLP-LOVE/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。
Jupyter Notebook UpdatedApr 20, 2020 -
awesome-interpretable-machine-learning Public
Forked from lopusz/awesome-interpretable-machine-learningPython UpdatedDec 2, 2019 -
-
lofo-importance Public
Forked from aerdem4/lofo-importanceLeave One Feature Out Importance
Python MIT License UpdatedOct 18, 2019 -
Feature-Selection-for-Machine-Learning Public
Forked from anujdutt9/Feature-Selection-for-Machine-LearningMethods with examples for Feature Selection during Pre-processing in Machine Learning.
Jupyter Notebook UpdatedOct 7, 2019 -
random-forest-importances Public
Forked from parrt/random-forest-importancesCode to compute permutation and drop-column importances in Python scikit-learn random forests
Jupyter Notebook MIT License UpdatedJul 17, 2019 -
PDPbox Public
Forked from SauceCat/PDPboxpython partial dependence plot toolbox
Jupyter Notebook MIT License UpdatedJul 17, 2019 -
Feature-Selection Public
Forked from duxuhao/Feature-SelectionFeatures selector based on the self selected-algorithm, loss function and validation method
Python MIT License UpdatedMay 8, 2019 -
unbiased-feature-importance Public
Forked from ZhengzeZhou/unbiased-feature-importanceImplementation of unbiased measurement of feature importance in Random Forests
Jupyter Notebook UpdatedApr 11, 2019 -
RandomForest-feature-importance Public
Forked from waltergenchi/RandomForest-feature-importanceExplore Importance of Features in Random Forests
Jupyter Notebook UpdatedJan 2, 2019 -
hpelm Public
Forked from akusok/hpelmHigh performance implementation of Extreme Learning Machines (fast randomized neural networks).
Jupyter Notebook Other UpdatedMay 24, 2018 -
interpreting-decision-trees-and-random-forests Public
Forked from gregtam/interpreting-decision-trees-and-random-forestsUnwrapping decision trees and random forests to make them less of a black box
Jupyter Notebook UpdatedSep 19, 2017
{{ message }}