-
- Description:
MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side, i.e., in the browser.
It includes the following.
LALOLib: a javascript library to enable and ease scientific computing within web pages
LALOLib provides functions for
- linear algebra,
- statistics,
- optimization (based on glpk.js).
Documentation is available at http://mlweb.loria.fr/lalolab/lalolib.html
ML.js: a javascript library for machine learning
In addition to all the functions of LALOLib, ML.js implements the following algorithms.
Classification
- K-nearest neighbors,
- Linear discriminant analysis,
- Naive Bayes classifier,
- Perceptron,
- Multi-layer perceptron,
- Support vector machines,
- Multi-class support vector machines,
- Decision trees
Regression
- Least squares,
- Least absolute devations,
- K-nearest neighbors,
- Ridge regression,
- LASSO,
- LARS,
- Orthogonal least squares,
- Multi-layer perceptron,
- Kernel ridge regression,
- Support vector regression,
- K-LinReg
Clustering
- K-means,
- Spectral clustering
Dimensionality reduction
- Principal component analysis,
- Locally linear embedding,
- Local tangent space alignment
Documentation is available at http://mlweb.loria.fr/lalolab/lalolib.html
LALOLab: a matlab-like development environment
Try it at http://mlweb.loria.fr/lalolab/
- Changes to previous version:
- Changed name of MLlib for ML.js
- Improved documentation for ML.js
- BibTeX Entry: Download
- Supported Operating Systems: Linux, Windows, Platform Independent, Mac Os X
- Data Formats: Ascii, Csv, Libsvm, Json
- Tags: Classification, Clustering, Regression, Dimensionality Reduction, Development Environment, Scientific Computing, Web
- Archive: download here
Comments
No one has posted any comments yet. Perhaps you'd like to be the first?
Leave a comment
You must be logged in to post comments.