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.