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Search results for python interpretable machine learning
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42 search results found
Awesome Machine Learning Interpretability
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3,241
A curated list of awesome responsible machine learning resources.
Dalex
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1,242
moDel Agnostic Language for Exploration and eXplanation
Awesome Interpretable Machine Learning
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856
Pygam
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784
[HELP REQUESTED] Generalized Additive Models in Python
Interpretable_machine_learning_with_python
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629
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Mli Resources
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405
H2O.ai Machine Learning Interpretability Resources
Pyss3
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307
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)
Etsformer
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131
PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
Conceptbottleneck
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99
Concept Bottleneck Models, ICML 2020
Tsinterpret
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83
An Open-Source Library for the interpretability of time series classifiers
Rrl
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82
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"
Talktomodel
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68
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Iba
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58
Information Bottlenecks for Attribution
Layerwise Relevance Propagation
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51
Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers
Prototree
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46
ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
Mace
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29
Model Agnostic Counterfactual Explanations
Contrxt
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19
a tool for comparing the predictions of any text classifiers
Diabetes_use_case
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19
Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
Interpretable Ml
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17
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
Survlimepy
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16
Local interpretability for survival models
Lri
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15
[ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.
Pipnet
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15
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Merlin
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14
MERLIN is a global, model-agnostic, contrastive explainer for any tabular or text classifier. It provides contrastive explanations of how the behaviour of two machine learning models differs.
Lucidmode
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14
A Lucid Framework for Transparent and Interpretable Machine Learning Models.
Mllp
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12
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
Article Information 2019
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10
Article for Special Edition of Information: Machine Learning with Python
Label Free Xai
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10
This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.
Pi Prl
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10
ICLR'22 Programmatic Reinforcement Learning
Ml Flask Api
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9
A simple template of a Python API (web-service) for real-time Machine Learning predictions, using scikitlearn-like models, Flask and Docker.
Autopeptideml
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9
AutoML system for building trustworthy peptide bioactivity predictors
Jsm_2018_paper
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8
Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlinepro
Explabox
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8
Explore/examine/explain/expose your model with the explabox!
Multiobjective_symbolic_regression
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6
This is a Python library that implements a Multi-objective Symbolic Regression algorithm. It can be used as a Machine Learning algorithm to create predictive models in the form of mathematical expressions.
Shapley_valuation
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6
PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuation of Data" by Amirata Ghorbani and James Zou [ICML 2019]
Deepcoda
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6
Deep learning for personalized interpretability for compositional health data
Epu Cnn
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5
Official Implementation of "E pluribus unum interpretable convolutional neural networks"
Xi Method
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5
Xi method
Xaisuite
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5
XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.
Pyslise
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5
Robust regression algorithm that can be used for explaining black box models (Python implementation)
Visualime
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5
Implementation of LIME focused on producing user-centric local explanations for image classifiers.
Dynamic Shap Plots
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5
Enabling interactive plotting of the visualizations from the SHAP project.
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