Note: The name of the dataset in the screenshot below is different from the dataset you are using. If you don’t have the right-side panel open by default, click the Data tab (upper right, second-to-last) in the toolbar to trigger the panel to open. You can drag and drop the dataset (.csv file) from your computer to that area, or click Browse to open file explorer on your computer where you can select the desired file. To upload the dataset, make sure that you have a right-side panel open where you will find an area prompting you to import your data. The first step is to upload the dataset to IBM Watson Studio. Steps Upload the dataset to IBM Watson Studio It takes approximately 1 hour to read and follow the steps in this how-to.
#HOW USE SPSS MODELER 18 TO ANALYZE RESEARCH DATA CODE#
If you want more flexibility in preparing your data and building your models than what Watson Studio’s Automatic Modeler offers, but still want the ease of use of a GUI interface and less code writing and complexity, you can use IBM SPSS Modeler.
IBM SPSS is available on IBM Watson Studio as one of many options to build predictive models.
Some of the details available are checking status, duration, credit history, purpose, credit amount, savings status, employment, and more. The dataset contains details about customers applying for loans. The loan risk dataset used in this how-to is free, open-source, and available on the BigML website. In this how-to, you will prepare data and build a predictive model using IBM SPSS Modeler to assess the risk of a loan application, and either approve the application and give the loan to a customer, or reject the application.