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Huyen LeHow can Neuro Symbolic AI help with eXplanable Artifical IntelligenceHow can we open up the black box?Apr 12, 2023Apr 12, 2023
InTDS ArchivebyConor O'SullivanFinding and Visualising InteractionsAnalysing interactions using feature importance, Friedman’s H-statistic and ICE PlotsJan 16, 20213Jan 16, 20213
InGeek CulturebyShahab MohagheghExplainable Artificial Intelligence (XAI)The Main Characteristics of Engineering Application of Artificial Intelligence (PART TWO)May 23, 2021May 23, 2021
InTDS ArchivebyRebecca VickeryPython Libraries for Interpretable Machine Learning4 libraries for better visualisation, explanation and interpretation of modelsAug 6, 201911Aug 6, 201911
InTDS ArchivebyScott LundbergInterpretable Machine Learning with XGBoostThis is a story about the danger of interpreting your machine learning model incorrectly, and the value of interpreting it correctly…Apr 17, 201849Apr 17, 201849
InTDS ArchivebyParul PandeyInterpretable Machine LearningExtracting human understandable insights from any Machine Learning modelApr 2, 201911Apr 2, 201911
Renee LINDifferences between Sobol and SHAP Sensitivity Analysis on Housing Prices PredictionsI recently applied both Sobol and SHAP to my model to get the most impactful feature, because I thought using two methods could be more…Mar 5, 20234Mar 5, 20234
InTDS ArchivebyPrateek BhatnagarExplainable AI(XAI) — A guide to 7 packages in Python to explain your modelsJun 3, 20217Jun 3, 20217
InTDS ArchivebyDario RadečićLIME vs. SHAP: Which is Better for Explaining Machine Learning Models?Two of the most popular Explainers compared.Dec 14, 20204Dec 14, 20204
InTDS ArchivebyNakul UpadhyaXAI for Forecasting: Basis ExpansionNBEATS and other Interpretable Deep Forecasting ModelsMar 24, 2023Mar 24, 2023
