The ability to create automatically reports from the results of an analysis is a valuable functionality for Data Mining. But this is rather an asset to the professional tools. The programming of this kind of functionality is not really promoted in the academic domain. I do not think that I can publish a paper in a journal where I describe the ability of Tanagra to create attractive reports. This is the reason for which the output of the academic tools, such as R or Weka, is mainly in a formatted text shape.
Tanagra, which is an academic tool, provides also text outputs. The programming remains simple if we see at a glance the source code. But, in order to make the presentation more attractive, it uses the HTML to format the results. I take advantage of this special feature to generate reports without making a particular programming effort. Tanagra is one of the few academic tools to be able to produce reports that can easily be displayed in office automation software. For instances, the tables can be copied into Excel spreadsheets for further calculations. More generally, the results can be viewed in a browser, regardless of data mining software.
These are the reporting features of Tanagra that we present in this tutorial.
Keywords: reporting, decision tree, c4.5, logistic regression, binary coding, roc curve, learning sample, test sample, forward, feature selection
Components: GROUP CHARACTERIZATION, SAMPLING, C4.5, TEST, O_1_BINARIZE, FORWARD-LOGIT, BINARY LOGISTIC REGRESSION, SCORING, ROC CURVE
Tutorial: en_Tanagra_Reporting.pdf
Dataset: heart disease
