Broundal / PytolemaicLinks
Toolbox for analysis of model's quality and model's description. For further details see
☆11Updated last year
Alternatives and similar repositories for Pytolemaic
Users that are interested in Pytolemaic are comparing it to the libraries listed below
Sorting:
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆159Updated 3 years ago
- Boosted neural network for tabular data☆217Updated last year
- The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to s…☆738Updated this week
- Streamline scikit-learn model comparison.☆142Updated 3 years ago
- Mixture of Decision Trees for Interpretable Machine Learning☆11Updated 4 years ago
- Train Gradient Boosting models that are both high-performance *and* Fair!☆107Updated this week
- The binclass-tools package contains a set of Python wrappers and interactive plots that facilitate the analysis of binary classification …☆73Updated 2 years ago
- ☆45Updated last month
- ☆150Updated 2 months ago
- Build Low Code Automated Tensorflow explainable models in just 3 lines of code. Library created by: Hasan Rafiq - https://www.linkedin.co…☆180Updated 3 years ago
- 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.☆345Updated 3 years ago
- Neo: Hierarchical Confusion Matrix Visualization (CHI 2022)☆315Updated last week
- Fast SHAP value computation for interpreting tree-based models☆553Updated 2 years ago
- ☆203Updated 3 months ago
- Doubt your data, find bad labels.☆516Updated last year
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆584Updated last year
- A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.☆469Updated 2 years ago
- Automated Tool for Optimized Modelling☆163Updated last year
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆324Updated 9 months ago
- Hopular: Modern Hopfield Networks for Tabular Data☆313Updated 3 years ago
- A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.☆243Updated last month
- A python package for benchmarking interpretability techniques on Transformers.☆215Updated last year
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆92Updated 2 years ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆102Updated 3 years ago
- just a bunch of useful embeddings for scikit-learn pipelines☆520Updated 4 months ago
- Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥…☆479Updated last week
- Small Dataset Benchmarks on the Dataset of Datasets UCI++☆93Updated 3 years ago
- PyTorch implementation of SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular Data paper☆25Updated last year
- A Simple Bulk Labelling Tool☆598Updated 6 months ago
- A Natural Language Interface to Explainable Boosting Machines☆69Updated last year