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Smruthi Raj Mohan | Published March 5, 2019
AnalyticsData managementMachine learning
IBM SPSS Modeler provides predictive analytics to help you uncover data patterns, gain predictive accuracy and improve decision making. This tutorial demonstrates an end-to-end flow of how to use SPSS Modeler on Watson Studio, ingest the data in a Db2 Warehouse database, perform analytics, and store back the results as a new table in the same database.
This tutorial will show you how to:
Completing this tutorial should take about 30 minutes.
Cloud Foundry Services
DB2 Warehouse instance
Add to Project
Change Data Asset > Connections > DB2Warehouse
From this graph we can see that the ages of the passengers, follows a normal distribution, i.e, most people have an age range of 20-55, and there are fewer people who are less than 20 and greater than 50. We can also see that, for some age groups, there are more men than women.
From this pie chart, we can see that 80% of the Cabin column has NaNs that is missing values. So, we can make a conclusion to drop this column since we know it cannot affect the target, in our case the Survived column.
Note: Nodes such as Derive and Merge can be used to create new columns from existing columns and merge two dataframes.
Data Asset Export
In this tutorial, you learned how to:
Step-by-step instructions to perform data analysis and generate a prediction model in SPSS.
Go through the process of preparing data and building a predictive model using IBM SPSS Modeler to solve a real-world…
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