This library is a compilation of the tools developed in the mljs organization.
It is mainly maintained for use in the browser. If you are working with Node.js, you might prefer to add
to your dependencies only the libraries that you need, as they are usually published to npm more often.
We prefix all our npm package names with ml- (eg. ml-matrix) so they are easy to find.
To include the ml.js library in a web page:
<script src="https://www.lactame.com/lib/ml/2.2.0/ml.min.js"></script>It will be available as the global ML variable. The package is in UMD format and can be "required" within webpack or requireJS.
- Principal component analysis (PCA):
ML.PCA - Hierarchical clustering:
ML.HClust - K-means clustering:
ML.KMeans
- Support vector machines:
ML.SVM - Naive Bayes:
ML.NaiveBayes - K-Nearest Neighbor (KNN):
ML.KNN - Partial least squares (PLS):
ML.PLS - Cross-validation:
ML.CrossValidation - Confusion matrix:
ML.ConfusionMatrix
- TBD
- Levenberg-Marquardt:
ML.levenbergMarquardt
- Matrix:
ML.Matrix(Matrix class) - Sparse matrix:
ML.SparseMatrix - Kernels:
ML.Kernel - Distance functions:
ML.Distance - Similarity functions:
ML.Similarity - Distance matrix:
ML.distanceMatrix - XORShift-add RNG:
ML.XSadd
- Performance (ROC curve):
ML.Performance
- Principal component analysis (PCA):
ML.PCA - Savitzky-Golay filter:
ML.savitzkyGolay - Savitzky-Golay generalized:
ML.savitzkyGolayGeneralized
- Bit array operations:
ML.BitArray - Hash table:
ML.HashTable - Pad array:
ML.padArray - Binary search:
ML.binarySearch - Number comparison functions for sorting:
ML.numSort