Khiops is an AutoML suite for supervised and unsupervised learning
β79Oct 7, 2026Updated this week
Alternatives and similar repositories for khiops
Users that are interested in khiops are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Ensemble Learning for Apache Spark π²β24Sep 3, 2024Updated 2 years ago
- Conformal Locally Valid interval-Estimates for Regressionβ17Sep 27, 2024Updated 2 years ago
- IEEE TVCG Visual Analytics in Deep Learning Surveyβ18Feb 11, 2021Updated 5 years ago
- Hyperparameters Spaces for Optimizationβ24Jan 21, 2019Updated 7 years ago
- AntakIA is THE tool to explain an ML model or replace it with a collection of basic explainable models.β14Jun 15, 2026Updated 3 months ago
- Deploy to Railway using AI coding agents - Free Credits Offer β’ AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Causal Impact but with MFLES and conformal prediction intervalsβ33Dec 31, 2024Updated last year
- Paper and talk from KDD 2019 XAI Workshopβ19May 31, 2020Updated 6 years ago
- Machine learning for portfolio management and trading with scikit-learnβ48Sep 28, 2026Updated 2 weeks ago
- β20Aug 28, 2024Updated 2 years ago
- Integrated tool for model development and validationβ36Nov 7, 2025Updated 11 months ago
- Official implementation of "Normalizing flow neural networks by JKO scheme" (NeurIPS 2023 spotlight)β12Sep 16, 2024Updated 2 years ago
- β10Feb 2, 2023Updated 3 years ago
- Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships.β11Jun 3, 2022Updated 4 years ago
- Bias detection and contextual evaluation tool for your AI projectsβ30Apr 27, 2026Updated 5 months ago
- GPU virtual machines on DigitalOcean Gradient AI β’ AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- LibCP -- A Library for Conformal Predictionβ13Feb 26, 2015Updated 11 years ago
- A plugin to scikit-learn for quantum-classical hybrid solvingβ18Jan 14, 2026Updated 8 months ago
- A project that analyses recent carbon emissions worldwideβ15Mar 26, 2024Updated 2 years ago
- β13Dec 8, 2022Updated 3 years ago
- Prediction Explanations Clusteringβ10Oct 19, 2023Updated 2 years ago
- Wrapper around MLForecast for more plug and play forecastingβ10Oct 23, 2023Updated 2 years ago
- Edgar SEC scraper and analyzer.β10Jun 3, 2022Updated 4 years ago
- β13Jun 4, 2023Updated 3 years ago
- Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"β13Apr 21, 2024Updated 2 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer β’ AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- β12Jun 17, 2024Updated 2 years ago
- A Python package for fitting Quinlan's Cubist regression modelβ61May 31, 2026Updated 4 months ago
- β15Jul 25, 2023Updated 3 years ago
- This repository has been created as part of the kaggleXBIPOC Mentorship Program. The aim of this project is to establish the sentiment aβ¦β11Mar 18, 2023Updated 3 years ago
- Benchmarks for the Evaluation of LLM Supervisionβ35Jan 19, 2026Updated 8 months ago
- This repository contains code for the paper: S Bergsma, T Zeyl, JR Anaraki, L Guo, C2FAR: Coarse-to-Fine Autoregressive Networks for Precβ¦β13Dec 7, 2023Updated 2 years ago
- Fully Flexible Probabilities for Stress-Testing and Portfolio Constructionβ21Updated this week
- Methods for online conformal prediction.β117May 1, 2025Updated last year
- Inspired by autoresearch but for financeβ20Mar 17, 2026Updated 6 months ago
- Proton VPN Special Offer - Get 70% off β’ AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- Repository for R and Python packages and reproduction codes in Weighted Conformalized Selection paperβ12Jul 21, 2023Updated 3 years ago
- Slides and suplemental notebooks for my PyData LA 2019 talk titled "Embed all the things"