Ganitha
Ganitha is an innovative open-source machine learning library designed for Scalding, specializing in statistical analysis and vector operations. It integrates Mahout vectors for seamless usability, offering implementations of Naive-Bayes classifiers and K-Means clustering. Users can efficiently handle data with advanced features, enhancing their machine learning workflows.
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Top Ganitha Features
- Open-source machine learning library
- Scalding integration
- Mahout vector compatibility
- User-friendly vector operations
- Naive-Bayes classifier support
- Gaussian Naive-Bayes implementation
- Multinomial Naive-Bayes implementation
- Bernoulli Naive-Bayes implementation
- K-Means clustering algorithm
- K-Means++ optimization
- K-Means|| initialization technique
- Extensible vector operation interface
- Vector serialization transparency
- Unit testing framework included
- Supports categorical and textual features
- Streamlined data processing workflow
- Easy deployment with sbt.
