wissam-sib / calibrated_metrics

Related projects ⓘ

Alternatives and complementary repositories for calibrated_metrics

• google-research / sloe-logistic
  ☆29Updated 6 months ago
• h2oai / wave-ml
  Automatic Machine Learning (AutoML) for Wave Apps
  ☆32Updated last year
• trisongz / pylines
  Simplifying parsing of large jsonline files in NLP Workflows
  ☆12Updated 2 years ago
• fastai / fastpy
  An easy way to start a python programming environment using GitHub Codespaces.
  ☆15Updated 4 years ago
• facebookarchive / fronni
  machine learning model performance metrics & charts with confidence intervals, optimized with numba to be fast
  ☆16Updated 2 years ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆41Updated last year
• paperd / tensorflow
  TensorFlow materials
  ☆13Updated 3 years ago
• ShopRunner / octopod
  Train multi-task image, text, or ensemble (image + text) models
  ☆45Updated last year
• tareknaous / visual-clustering
  Visual Clustering: Clustering Plotted Data by Image Segmentation
  ☆24Updated 9 months ago
• SCCH-KVS / training-engine
  The stand-alone training engine module for the ALOHA.eu project.
  ☆15Updated 5 years ago
• AlexIoannides / llm-regression
  Exploring the classical regression capabilities of LLMs.
  ☆17Updated 6 months ago
• sayakpaul / parameter-ensemble-differential-evolution
  Shows how to do parameter ensembling using differential evolution.
  ☆10Updated 2 years ago
• mllite / sklearn_explain
  Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.
  ☆13Updated 3 years ago
• facebookresearch / tce
  Library for the Test-based Calibration Error (TCE) metric to quantify the degree to classifier calibration.
  ☆13Updated last year
• thomasjpfan / skconfig
  Experimental library for sampling and validating scikit-learn parameters
  ☆10Updated 5 years ago
• tchaton / pytorch2lightning
  ☆15Updated 3 years ago
• navdeep-G / interpretable-ml
  Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
  ☆21Updated 2 years ago
• ypeleg / Fastformer-Keras
  Unofficial Tensorflow-Keras implementation of Fastformer based on paper [Fastformer: Additive Attention Can Be All You Need](https://arxi…
  ☆13Updated 3 years ago
• jameslamb / lightgbm-dask-testing
  Test LightGBM's Dask integration on different cluster types
  ☆12Updated 2 months ago
• szilard / awesome-GBMs
  A curated list of gradient boosting machines (GBM) resources
  ☆10Updated 5 years ago
• pbiecek / xai_stories
  XAI Stories. Case studies for eXplainable Artificial Intelligence
  ☆29Updated 4 years ago
• jeongyoonlee / dotfiles
  dot files and setup scripts
  ☆10Updated this week
• Data-Heroes / dataheroes
  Public repository holding examples for dataheroes library
  ☆19Updated this week
• criteo / fromconfig
  A library to instantiate any Python object from configuration files.
  ☆24Updated 2 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated last year
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 3 years ago
• radekosmulski / fastai-rails
  ☆25Updated last year
• jphall663 / kdd_2019
  Paper and talk from KDD 2019 XAI Workshop
  ☆20Updated 4 years ago
• CamDavidsonPilon / PyDataNY_2019_tutorial
  Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference
  ☆26Updated 5 years ago