Creating SPSS Modeler flows
With SPSS Modeler flows, you can quickly develop predictive models that use business expertise and deploy them into business operations to improve decision making. Designed around the long-established SPSS Modeler client software and the industry-standard CRISP-DM model it uses, the flows interface supports the entire data mining process, from data to better business results.
SPSS Modeler offers various modeling methods that are taken from machine learning, artificial intelligence, and statistics. You can use the methods available on the node palette to derive new information from your data and to develop predictive models. Each method has certain strengths and is best suited for particular types of problems.
Using the Flow Editor, you prepare or shape data, train or deploy a model, or transform data and export it back to a database table or a file in Cloud Object Storage. Running an SPSS Modeler flow consumes capacity unit hours. For more information, see watsonx.ai Studio environments compute usage.
New to SPSS Modeler?
- The provided Tutorials help you develop your skills and highlight SPSS Modeler's vast capabilities.
- Watch the following short videos for a few modeling examples.
These videos provide a visual method to learn the concepts and tasks in this documentation.
Video disclaimer: Some minor steps and graphical elements in these videos might differ from your platform.
- Data format
-
- Relational: Tables in relational data sources
- Tabular: Tables in data files such as .xls, .csv, .json, or .sas. For Excel files, only the first sheet is read.
- Textual: In the supported relational tables or files
- Data size
- Any
- How can I prepare data?
- Use automatic data preparation functions
- How can I analyze data?
- Visualize data with many chart options
- How can I build models?
- Build predictive models
- Getting started
- To create an SPSS Modeler flow from the project's Assets tab, click .