ingredients
Feature assesser
Provides tools to assess and visualize the importance and effects of features in machine learning models
Effects and Importances of Model Ingredients
37 stars
8 watching
19 forks
Language: R
last commit: over 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
giuseppec/featureimportance | A tool to assess feature importance in machine learning models | 33 |
modeloriented/modelstudio | A tool for creating interactive, model-agnostic explanations of machine learning models in R | 327 |
aerdem4/lofo-importance | A tool to evaluate feature importance by iteratively removing each feature and evaluating model performance on validation sets. | 816 |
modeloriented/fairmodels | A tool for detecting bias in machine learning models and mitigating it using various techniques. | 86 |
modeloriented/dalex | A tool to help understand and explain the behavior of complex machine learning models | 1,379 |
feature-engine/feature_engine | A Python library with multiple transformers to engineer and select features for use in machine learning models. | 1,945 |
modeloriented/ibreakdown | A tool for explaining predictions from machine learning models by attributing them to specific input variables and their interactions. | 82 |
declare-lab/instruct-eval | An evaluation framework for large language models trained with instruction tuning methods | 532 |
giuseppec/iml | Provides methods to interpret and explain the behavior of machine learning models | 492 |
neuro-inc/ml-recipe-hier-attention | An implementation of a neural network architecture for sentiment classification using hierarchical attention mechanisms. | 2 |
tensorflow/model-analysis | Evaluates and visualizes the performance of machine learning models. | 1,257 |
rmarko/explainprediction | An R package for explaining the predictions made by machine learning models in data science applications. | 2 |
modeloriented/drwhy | A collection of tools and guidelines for building responsible machine learning models | 680 |
modeloriented/randomforestexplainer | A set of tools to provide insights into the workings of an ensemble machine learning model. | 230 |
huggingface/evaluate | An evaluation framework for machine learning models and datasets, providing standardized metrics and tools for comparing model performance. | 2,042 |