With SPSS Modeler flows in Watson Studio, you can quickly develop predictive models using 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 in Watson Studio supports the entire data mining process, from data to better business results.
Watson Studio offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics. The methods available on the node palette allow you 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. To create an SPSS model, add the Modeler flow asset type to your project, then select SPSS as the flow type. Note that running an SPSS Modeler flow consumes capacity unit hours. See Watson Studio environments compute usage for more information.
- Data format
- Relational: Tables in relational data sources
- Tabular: Excel files (.xls) or CSV files
- Textual: In the supported relational tables or files
- Data size
- How can I prepare data?
- Use automatic data preparation functions
- Write SQL statements to manipulate data
- Cleanse, shape, sample, sort, and derive data
- How can I analyze data?
- Visualize data with many chart options
- Identify the natural language of a text field
- How can I build models?
- Build predictive models
- Choose from over 40 modeling algorithms, and many other nodes
- Use automatic modeling functions
- Model time series or geospatial data
- Classify textual data
- Identify relationships between the concepts in textual data
- Getting started
- To create an SPSS Modeler flow, click and then choose IBM SPSS Modeler.