paypal / autosklearn-zeroconf
autosklearn-zeroconf is a fully automated binary classifier. It is based on the AutoML challenge winner auto-sklearn. Give it a dataset with known outcomes (labels) and it returns a list of predicted outcomes for your new data. It even estimates the precision for you! The engine is tuning massively parallel ensemble of machine learning pipelines…
☆169Updated 5 years ago
Alternatives and similar repositories for autosklearn-zeroconf:
Users that are interested in autosklearn-zeroconf are comparing it to the libraries listed below
- Deploy AutoML as a service using Flask☆226Updated 7 years ago
- ☆162Updated 3 years ago
- A package for parallelizing the fit and flexibly scoring of sklearn machine learning models, with visualization routines.☆199Updated last year
- lightweight python wrapper for vowpal wabbit☆168Updated 5 years ago
- A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.☆125Updated last year
- Bayesian Optimization using xgboost and sklearn API☆226Updated 9 years ago
- A collaborative feature engineering system built on JupyterHub☆94Updated 6 years ago
- A new version of phraug, which is a set of simple Python scripts for pre-processing large files☆206Updated 6 years ago
- Speedml is a Python package to speed start machine learning projects.☆212Updated 5 years ago
- ☆77Updated 8 years ago
- A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.☆212Updated 7 years ago
- a machine learning dashboard that displays hyperparameter settings alongside visualizations, and logs the scientist's thoughts throughout…☆128Updated 2 years ago
- Advanced Scikit-learn training session☆118Updated 8 years ago
- A library for factorization machines and polynomial networks for classification and regression in Python.☆245Updated 4 years ago
- dask-searchcv is now part of dask-ml: https://github.com/dask/dask-ml☆240Updated 6 years ago
- greedy feature selection based on ROC AUC☆125Updated 11 years ago
- Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one…☆381Updated 3 years ago
- ☆89Updated 6 years ago
- Some small utility modules to help with pandas, numpy and sklearn usage in other projects☆182Updated 2 years ago
- Some work on Kaggle data for fun☆64Updated 7 years ago
- Lightweight, Python library for fast and reproducible experimentation☆134Updated 6 years ago
- A simple, extensible library for developing AutoML systems☆175Updated last year
- Scikit-learn API toy wrapper for Regularized Greedy Forests☆44Updated 8 years ago
- Experimental Gradient Boosting Machines in Python with numba.☆184Updated 6 years ago
- Hodor AutoML: Brute-Bandit fast good-enough solutions to a wide range of machine learning problems.☆83Updated 9 years ago
- SigOpt wrappers for scikit-learn methods☆75Updated last year
- How to predict credit defaulting?☆93Updated 5 years ago
- Some experiments into explaining complex black box ensemble predictions.☆75Updated 5 years ago
- ☆160Updated 8 years ago
- Code to share different ensemble techniques with focus on meta-stacking , using data from Amazon.com - Employee Access Challenge kaggle c…☆222Updated 9 years ago