Saturday, May 20, 2017

Support vector machine (slides)

In machine learning, support vector machines (SVM) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis (Wikipedia).

These slides show the background of the approach in the classification context. We address the binary classification problem, the soft-margin principle, the construction of the nonlinear classifiers by means of the kernel functions, the feature selection process, the multiclass SVM.

The presentation is complemented by the implementation of the approach under the open source software Python (Scikit-Learn), R (e1071) and Tanagra (SVM and C-SVC).

Keywords: svm, e1071 package, R software, Python, scikit-learn package, sklearn
Components: SVM, C-SVC
Slides: Support Vector Machine (SVM)
Dataset: svm exemples.xlsx
References:
Abe S., "Support Vector Machines for Pattern Classification", Springer, 2010.

Thursday, January 5, 2017

Tanagra website statistics for 2016

The year 2016 ends, 2017 begins. I wish you all a very happy year 2017.

A small statistical report on the website statistics for the 2016. All sites (Tanagra, course materials, e-books, tutorials) has been visited 264,045 times this year, 721 visits per day.

Since February, the 1st, 2008, the date from which I installed the Google Analytics counter, there are 2,111,078 visits (649 daily visits).

Who are you? The majority of visits come from France and Maghreb. Then there are a large part of French speaking countries, notably because some pages are exclusively in French. In terms of non-francophone countries, we observe mainly the United States, India, UK, Brazil, Germany, ...

The pages containing course materials about Data Mining and R Programming are the most popular ones. This is not really surprising.

Happy New Year 2017 to all.

Ricco.
Slideshow: Website statistics for 2016