XcessivWhat is Xcessiv?
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
Xcessiv is a tool in the Development & Training Tools category of a tech stack.
Key Features
Fully define your data source, cross-validation process, relevant metrics, and base learners with Python codeAny model following the Scikit-learn API can be used as a base learnerTask queue based architecture lets you take full advantage of multiple cores and embarrassingly parallel hyperparameter searchesDirect integration with TPOT for automated pipeline constructionAutomated hyperparameter search through Bayesian optimizationEasy management and comparison of hundreds of different model-hyperparameter combinationsAutomatic saving of generated secondary meta-featuresStacked ensemble creation in a few clicksAutomated ensemble construction through greedy forward model selectionExport your stacked ensemble as a standalone Python file to support multiple levels of stacking
Xcessiv Pros & Cons
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Xcessiv Alternatives & Comparisons
What are some alternatives to Xcessiv?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
