Simple Bayes
This Naive Bayes implementation in Elixir offers a robust tool for probabilistic classification, ideal for tasks such as text categorization and medical diagnosis. Leveraging Bayes' theorem with strong independence assumptions, it ensures efficient training and scalability, making it a competitive choice against more complex classifiers while providing flexible storage options.
Top Simple Bayes Alternatives
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Classifier
The Classifier module enables efficient Bayesian and Latent Semantic Indexing (LSI) classifications for robust data analysis.
Amazon CodeGuru
Amazon CodeGuru is an advanced machine learning tool that enhances software development by automating code reviews and identifying vulnerabilities.
MLBase.jl
MLBase.jl offers a versatile collection of functions designed to enhance the development of machine learning algorithms.
FlinkML
FlinkML is an advanced machine learning library designed for the Flink ecosystem, offering a range of scalable algorithms and an intuitive API.
JRuby Mahout
JRuby Mahout integrates the power of Apache Mahout into JRuby, facilitating machine learning for recommendations, clustering, and classification.
Apache SystemML
An open-source ML system, Apache SystemML streamlines the entire data science lifecycle, encompassing data integration, cleaning, feature engineering, and efficient model training.
Ganitha
It integrates Mahout vectors for seamless usability, offering implementations of Naive-Bayes classifiers and K-Means clustering...
Apache SAMOA
Its pluggable architecture enables seamless operation on various distributed stream processing engines like Apache Storm...
Comportex
Based on the Numenta CLA white paper, this library emphasizes user-driven exploration of HTM...
IBM Machine Learning for z/OS
It provides secure, rapid access to computing resources while integrating seamlessly into hybrid cloud and...
shaman
Users can choose between the Normal Equation and Gradient Descent for model training, with customizable...
ibm powerai
Leveraging GPU technology for enhanced performance, it provides user-friendly tools that enable individuals with limited...
yahmm
It offers functionalities for training and evaluating sequences, utilizing various algorithms like Baum-Welch and Viterbi...
Stanford Classifier
It excels with text data while also accommodating numeric variables, providing a probability distribution for...
rapaio
It features core statistical tools, various algorithms like Naive Bayes and Random Forests, and provides...
Top Simple Bayes Features
- Elixir-based implementation
- Strong independence assumptions
- Text categorization support
- Efficient maximum-likelihood training
- Scalable parameter requirements
- Simple installation process
- Optional word stemming functionality
- In-memory storage option
- File system encoding speed
- Dets library integration
- Compatibility with older Elixir versions
- User-configurable options
- Base64 data encoding
- Performance optimization comparisons
- Feedback-driven improvements
- Open-source MIT license
- Document category classification
- Automatic medical diagnosis application
- Competitive with advanced methods.
