PredictionIO vs Xcessiv: What are the differences?
What is PredictionIO? Open Source Machine Learning Server. PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
What is Xcessiv? Fully managed web application for automated machine learning. A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
PredictionIO and Xcessiv can be categorized as "Machine Learning" tools.
Some of the features offered by PredictionIO are:
- Integrated with state-of-the-art machine learning algorithms. Fine-tune, evaluate and implement them scientifically.
- Customize the modularized open codebase to fulfill any unique prediction requirement.
- Built on top of scalable frameworks such as Hadoop and Cascading. Ready to handle data of any scale.
On the other hand, Xcessiv provides the following key 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
PredictionIO and Xcessiv are both open source tools. It seems that PredictionIO with 11.8K GitHub stars and 1.92K forks on GitHub has more adoption than Xcessiv with 1.19K GitHub stars and 95 GitHub forks.