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Search results for machine learning feature importance
feature-importance
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machine-learning
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14 search results found
Xai
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1,060
XAI - An eXplainability toolbox for machine learning
Lofo Importance
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785
Leave One Feature Out Importance
Feature Selection
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475
Features selector based on the self selected-algorithm, loss function and validation method
Hierarchical Dnn Interpretations
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119
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Deep Explanation Penalization
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74
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
Disentangled Attribution Curves
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23
Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
Hdb_resale_prices
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18
Predicted and identified the drivers of Singapore HDB resale prices (2015-2019) with 0.96 Rsquare & $20,000 MAE. Web app deployment using Streamlit for user price prediction.
Simplex
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15
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.
Msdlib
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13
This is a custom library for data processing, visualization and machine learning tools.
Pytolemaic
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10
Toolbox for analysis of model's quality and model's description. For further details see
S4
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9
Solid-state synthesis science analyzer. Thermo, features, ML, and more.
Shapley
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6
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Heart Uci Dataset
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6
Analyzing the Features which leads to heart diseases and visualizing the models' performance and important features using eli5, shap and pdp.
Cf Shap
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5
Counterfactual SHAP: a framework for counterfactual feature importance
Shapflex
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5
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
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