DATA MINING. The CRISP-DM METHODOLOGY. The CLEM language and IBM SPSS MODELER

This book describes the CRISP-DM modelling process for data mining. SPSS (then ISL and now IBM-SPSS) had been providing Data Mining based services since 1990 and had launched the first commercial Data Mining tool Clementine in 1994. Now the principal product that implements the CRISP-DM Methodology is IBM SPSS Modeler. This book describes also the Control Language for Expression Manipulation (CLEM), which is a powerful tool used to analyze and manipulate the data used in IBM SPSS Modeler streams. You can use CLEM within nodes to perform tasks ranging from evaluating conditions or deriving values to inserting data into reports. CLEM expressions consist of values, field names, operators, and functions. Using the correct syntax, you can create a wide variety of powerful data operations. IBM SPSS Modeler is an integrated data mining tool that includes several data sources (ASCII, XLS, ODBC, etc.), a visual interface based on data processes/flows (streams), different data mining tools (correlation, association rules, regression, segmentation, classification, neural networks, decision rules and trees, etc.), data manipulation (pick & mix, sampling, combination and separation, etc.), model combination, data visualisation, model export to different languages (C, SPSS, SAS, etc.), integrated data export to other programs (XLS) and report generation.