disentangled-attribution-curves

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

MIT License

Stars
23
View Code on GitHub Visit Website View on X
Ecosystems: Python, scikit-learn

Statistics for this project are still being loaded, please check back later.

Related Projects
rflvm

Random feature latent variable models in Python

31 May 2020 21
interpretable-embeddings

Interpretable text embeddings by asking LLMs yes/no questions

07 May 2024 8
awesome-decision-tree-papers

A collection of research papers on decision, classification and regression trees with implementat...

11 May 2019 2,339
dtreeviz

A python library for decision tree visualization and model interpretation.

13 Aug 2018 2,851
ml_implementation

Implementation of Machine Learning Algorithms

11 Jun 2017 370
Text_Classification

Text Classification Algorithms: A Survey

06 Jul 2018 1,794
ML_for_learner

Implementations of the machine learning algorithm with Python and numpy

20 Dec 2018 87
Machine-Learning

机器学习原理

28 May 2017 1,291
narx-double-descent

Explore the double-descent phenomena in the context of system identification. Companion code to t...

04 Dec 2020 6
mlinsights

Extends scikit-learn with new models, transformers, metrics, plotting.

18 Nov 2017 69
imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-co...

04 Jul 2019 1,372
ali-pytorch

Adversarially Learned Inference in Pytorch

24 Mar 2017 30
CausalDiscoveryToolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure re...

31 May 2017 1,115
hierarchical-dnn-interpretations

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictio...

18 May 2018 124
random-feature-maps

Fast Random Kernelized Features: Support Vector Machine Classification for High-Dimensional IDC D...

07 Dec 2018 5