Search Results for "statistical learning"

STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template...

Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities.

LExAu: Learning Expectations Autonomously. Library for on-line data driven statistical machine learning.

Myrtle is a simple programmable spreadsheet and statistical analysis software specifically designed for learning statistics. It provides the standard spreadsheet functionality one would expect like multiple tabbed sheets, relative and absolute row and column referencing in formulas, and a large catalog of built-in functions. Functions specific to logic and computer science, mathematics, probability, and statistics are available.

R based genetic algorithm for optimization, variable selection and other machine learning and statistical analysis approaches.

Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.