Fully managed web application for automated machine learning
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Why people like Xcessiv
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A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

Xcessiv's Features
  • Fully define your data source, cross-validation process, relevant metrics, and base learners with Python code
  • Any model following the Scikit-learn API can be used as a base learner
  • Task queue based architecture lets you take full advantage of multiple cores and embarrassingly parallel hyperparameter searches
  • Direct integration with TPOT for automated pipeline construction
  • Automated hyperparameter search through Bayesian optimization
  • Easy management and comparison of hundreds of different model-hyperparameter combinations
  • Automatic saving of generated secondary meta-features
  • Stacked ensemble creation in a few clicks
  • Automated ensemble construction through greedy forward model selection
  • Export your stacked ensemble as a standalone Python file to support multiple levels of stacking