Topic: iml Goto Github
Some thing interesting about iml
Some thing interesting about iml
iml,The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
User: 12wang3
iml,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"
User: 12wang3
iml,An interactive framework to visualize and analyze your AutoML process in real-time.
Organization: automl
Home Page: https://automl.github.io/DeepCAVE/main/
iml,A two-way interactive platform teaching user to draw & machine to evolute
User: etienne-bobo
iml,What and How of Machine Learning Transparency – ECML-PKDD 2020 Hands-on Tutorial
Organization: fat-forensics
Home Page: https://events.fat-forensics.org/2020_ecml-pkdd
iml,Полная SDK агрегатора служб доставки FsDelivery.ru
User: fsdelivery
iml,Micro-reserve model using XGBoost
User: gabrielcrepeault
Home Page: https://gabrielcrepeault.github.io/xgbmr/.
iml,Effector - a Python package for global and regional effect methods
User: givasile
Home Page: https://xai-effector.github.io/
iml,Article for Special Edition of Information: Machine Learning with Python
Organization: h2oai
Home Page: https://www.mdpi.com/journal/information/special_issues/ML_Python
iml,H2O.ai Machine Learning Interpretability Resources
Organization: h2oai
iml,💡 Adversarial attacks on explanations and how to defend them
User: hbaniecki
Home Page: https://doi.org/10.1016/j.inffus.2024.102303
iml,Robustness of Global Feature Effect Explanations (ECML PKDD 2024)
User: hbaniecki
Home Page: https://arxiv.org/abs/2406.09069
iml,Repository for my msc-research. Written in R, Python and PlantUML.
User: iammelvink
Home Page: https://doi.org/10.1109/access.2024.3365586
iml,SDK для работы с API IML delivery (api.iml.ru)
User: iamwildtuna
Home Page: https://t.me/phpdeliverysdk_chat
iml,Fit interpretable models. Explain blackbox machine learning.
Organization: interpretml
Home Page: https://interpret.ml/docs
iml,Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
User: jphall663
iml,Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
User: jphall663
iml,Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
User: jphall663
iml,Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
User: jphall663
iml,High precision anchor black box explanation algorithm
Organization: luh-ai
iml,examples for modelDown, package that turns model into HTML pages
Organization: mi2datalab
Home Page: https://mi2datalab.github.io/modelDown_example/
iml,Interactive XAI dashboard
Organization: modeloriented
Home Page: https://arena.drwhy.ai
iml,Data generator for Arena - interactive XAI dashboard
Organization: modeloriented
Home Page: https://arenar.drwhy.ai
iml,moDel Agnostic Language for Exploration and eXplanation
Organization: modeloriented
Home Page: https://dalex.drwhy.ai
iml,Explain! Package with core wrappers for DrWhy universe.
Organization: modeloriented
Home Page: https://modeloriented.github.io/DALEX2/
iml,Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
Organization: modeloriented
Home Page: https://ModelOriented.github.io/iBreakDown/
iml,Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
Organization: modeloriented
Home Page: https://modeloriented.github.io/live/
iml,📍 Interactive Studio for Explanatory Model Analysis
Organization: modeloriented
Home Page: https://doi.org/10.1007/s10618-023-00924-w
iml,Surrogate Assisted Feature Extraction in R
Organization: modeloriented
Home Page: https://ModelOriented.github.io/rSAFE/
iml,Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Organization: modeloriented
Home Page: https://modeloriented.github.io/treeshap/
iml,Variable importance via oscillations
Organization: modeloriented
Home Page: https://modeloriented.github.io/vivo/
iml,Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
User: navdeep-g
iml,An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
User: nredell
iml,A Julia package for interpretable machine learning with stochastic Shapley values
User: nredell
Home Page: https://nredell.github.io/ShapML.jl/dev/
iml,Open and extensible benchmark for XAI methods
User: oxid15
Home Page: https://oxid15.github.io/xai-benchmark/
iml,Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting Machine
User: parisa-salmanian
iml,Model Agnostics breakDown plots
User: pbiecek
Home Page: https://pbiecek.github.io/breakDown/
iml,Show case for modelStudio based on ⚽⚽⚽FIFA 20 ⚽⚽⚽
User: pbiecek
Home Page: https://pbiecek.github.io/explainFIFA20
iml,XAI Stories 2.0. eXplainable Artificial Intelligence for Retail Analytics - case studies
User: pbiecek
Home Page: https://pbiecek.github.io/xai_stories_2/
iml,A Python package with explanation methods for extraction of feature interactions from predictive models
Organization: pyartemis
iml,DrCaptcha is an interactive machine learning application. The purpose of the program is to the feedback provided by users, and to use it to optimize a machine learning model. The purpose of this model is to recognize handwritten letters and numbers.
User: rafaelglikis
iml,Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
User: rehmanzafar
iml,Implementation of the Anchors algorithm: Explain black-box ML models
Organization: viadee
iml,XMLX GitHub configuration
Organization: xmlx-dev
Home Page: https://github.com/xmlx-dev
iml,XMLX GitHub configuration
Organization: xmlx-io
Home Page: https://github.com/xmlx-io
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