I know the name "Scilab" for a long time (http://www.scilab.org/en). For me, it is a tool for numerical analysis. It seemed not interesting in the context of the statistical data processing and data mining. Recently a mathematician colleague spoke to me about this tool. He was surprised about the low visibility of Scilab within the data mining community, knowing that it proposes functionalities which are quite similar to those of R software. I confess that I did not know Scilab from this perspective. I decided to study Scilab by setting a basic goal: is it possible to perform simply a predictive analysis process with Scilab? Namely: loading a data file (learning sample), building a predictive model, obtaining a description of its characteristics, loading a test sample, applying the model on this second set of data, building the confusion matrix and calculating the test error rate.
We will see in this tutorial that the whole task has been completed successfully easily. Scilab is perfectly prepared to fulfill statistical treatments. But two small drawbacks appear during the catch in hand of Scilab: the library of statistical functions exists but it is not as comprehensive as that of R; their documentation is not very extensive at this time. However, I am very satisfied of this first experience. I discovered an excellent free tool, flexible and efficient, very easy to take in hand, which turns out a credible alternative to R in the field of data mining.
Keywords: scilab, toolbox, nan, libsvm, linear discriminant analysis, R software, predictive analytics
Tutorial : en_Tanagra_Scilab_Data_Mining.pdf
Dataset : data_mining_scilab.zip
References :
Scilab - https://www.scilab.org/fr
ATOMS : Homepage - http://atoms.scilab.org/
