SPSS Modeler offers modeling algorithms that are taken
from machine learning, artificial intelligence, and statistics. You can use these modeling
algorithms to analyze your data and gain new business insights. With SPSS Modeler, you can quickly develop predictive models and deploy them into
business operations.
What is SPSS Modeler?
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SPSS Modeler is a data mining application, where you can build data mining
SPSS Modeler flows by using the visual interface. Programming is not
required. You can build SPSS Modeler flows to explore your data,
model outcomes, try different models, and investigate relationships to find useful information.
SPSS Modeler uses the Cross-Industry Standard Process for Data Mining
(CRISP-DM) methodology, which is an industry-proven way to guide your data mining
efforts.
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 Watson Studio environments compute
usage.
You can use the advanced analytics in SPSS Modeler to discover patterns in your data and tune models. You can then
deploy these models in your business to make predictions on new data with unknown outcomes. The
models can systemically analyze data and find business insights and opportunities. If you have
access to the watsonx.ai Runtime service, you can promote
models to deployment spaces to run them.
Data formats
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
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
Note:Watsonx.ai doesn't include SPSS Modeler functionality in Peru, Ecuador, Colombia, or
Venezuela.
Scripting
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You can use scripting in SPSS Modeler to automate tasks that are
highly repetitive or time consuming to perform manually. Scripts can perform all the same types of
actions as users with a mouse or a keyboard, and you can write scripts in R, Python, or Python for
Spark.
The following are some of the tasks that you can automate with scripts:
Impose a specific order for running nodes in a flow
Set properties for a node
Set up a process that automatically takes a model training flow, runs it, and produces the
corresponding model-testing flow.
Related services
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If you have access to other services on Watsonx.ai,
you can use them with SPSS Modeler. The following services offer
features that complement work in SPSS Modeler.
Note:Watson.ai
Studio is prerequisite service for SPSS Modeler.
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