3 Prepare the Data
Learn how to access and treat the data that can be used to build a model.
- Data Requirements
Understand how data is stored and viewed for Oracle Machine Learning. - About Attributes
Attributes are the items of data that are used in machine learning. Attributes are also referred as variables, fields, or predictors. - Use Nested Data
A join between the tables for one-to-many relationship is represented through nested columns. - Use Market Basket Data
Understand the use of association and Apriori for market basket analysis. - Use Retail Data for Analysis
Retail analysis often makes use of association rules and association models. - Handle Missing Values
Understand sparse data and missing values. - About Transformations
Understand how you can transform data by using Automatic Data Preparation (ADP) and embedded data transformation. - Prepare the Case Table
The first step in preparing data for machine learning is the creation of a case table.