gensvm - A Generalized Multiclass Support Vector Machine

The GenSVM classifier is a generalized multiclass support vector machine (SVM). This classifier aims to find decision boundaries that separate the classes with as wide a margin as possible. In GenSVM, the loss function is very flexible in the way that misclassifications are penalized. This allows the user to tune the classifier to the dataset at hand and potentially obtain higher classification accuracy than alternative multiclass SVMs. Moreover, this flexibility means that GenSVM has a number of other multiclass SVMs as special cases. One of the other advantages of GenSVM is that it is trained in the primal space, allowing the use of warm starts during optimization. This means that for common tasks such as cross validation or repeated model fitting, GenSVM can be trained very quickly. Based on: G.J.J. van den Burg and P.J.F. Groenen (2018) <https://www.jmlr.org/papers/v17/14-526.html>.

Last updated 2 years ago

classificationmachine-learningmachine-learning-algorithmsmulticlass-classificationsupport-vector-machine

3.96 score 7 stars 26 scripts 734 downloads

sparsestep - SparseStep Regression

Implements the SparseStep model for solving regression problems with a sparsity constraint on the parameters. The SparseStep regression model was proposed in Van den Burg, Groenen, and Alfons (2017) <arXiv:1701.06967>. In the model, a regularization term is added to the regression problem which approximates the counting norm of the parameters. By iteratively improving the approximation a sparse solution to the regression problem can be obtained. In this package both the standard SparseStep algorithm is implemented as well as a path algorithm which uses golden section search to determine solutions with different values for the regularization parameter.

Last updated 4 years ago

feature-selectionlasso-variantsregularized-linear-regressionsparse-regressionsparse-regularization

2.70 score 1 stars 7 scripts 189 downloads

SyncRNG - A Synchronized Tausworthe RNG for R and Python

Generate the same random numbers in R and Python.

Last updated 1 years ago

1.20 score 16 scripts 126 downloads