Kursbeskrivning: Introduction to IBM SPSS Modeler and Data Mining - ILT

This course provides an overview of data mining and the fundamentals of using PASW Modeler. Using the CRISP-DM methodology, the principles and practice of data mining are illustrated. The course structure follows the stages of a typical data mining project, from reading data, to data exploration, data transformation, modeling, and effective interpretation of results. The course provides training in the basics of how to read, explore, and manipulate data with PASW Modeler, and then create and use successful models.

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This is a basic course for anyone with little or no experience using PASW Modeler (formerly Clementine) or with data mining in general.

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You should have:

• General computer literacy.

It would be helpful if you had an understanding of your organization's data, as well as any of your organization's business issues that are relevant to the use of data mining. No statistical background is necessary.

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Please refer to course overview for description information.

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• Introduction to data mining
• The CRISP-DM methodology
• Best practices for data mining
• The basics of using PASW Modeler
• Reading data files
• Working with dates
• Auditing and exploring data quality
• Searching for anomalous data and outliers
• Data manipulation
• Searching for relationships among fields
• Combining data files by appending and/or merging
• Restructuring data files with aggregate
• Sampling data
• Partitioning data for modeling
• Modeling techniques in PASW Modeler
• Automatic Modeling for Binary Outcomes
• Evaluating and comparing model performance
• Deploying and using models
• Running PASW Statistics commands from PASW Modeler

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