Hi, I am interested to explore regression tools in conjunction with Machine learning. Currently XLSTAT is not offering any regression solutions within Machine Learning. One of the areas to look into is SVM, where regression solutions are offered. ...

The Tanimoto coefficient is the most widely used similarity metric in cheminformatics.

Hi, I have a question regarding the modeling data section. I have an XLSTAT-Premium version to deal with the metabolomics data. PCA and PLS-DA contributed a lot to explore my dataset. However, nowadays Orthogonal Partial least squares discriminant...

We do a lot of ranking. From the ranking study, we can calculate r-index. Also d prime can be calculated from r-index. I believe there is a package in R already exist. It would be good to add this to XLSTAT.

Data is becoming ever more both high dimensional and sparse. Kernel PCA can enable a reliable and relatively simple dimensionality reduction. Kernels have already been introduced in Xlstat via SVMs.

Very useful when I need to understand relationships between 2 or 3 samples. And it would prevent me from spending hours on PowerPoint ! Thanks

Spatial data stats is perhaps the most important aspect in ecology but also for geochemistry, environmental research, conservation. At least some basic tests should be provided:Clark and Evans' R, Pielou's α, etc.

ma proposition est dans le titre. par ailleurs, je pense que vous devriez vous adapter à la mise en ligne en version gratuite de certains logiciel tels que SAS....

Confidence ellipses in pca illustrate the dissociation of groups and aid in the recognition of trends.