Chapter 4: Classification

Activity 7: Preparing Credit Data for Classification

This section will discuss how to prepare data for a classifier. We will be using german.data from https://archive.ics.uci.edu/ml/machine-learning-databases/statlog/german/, as an example and prepare the data for training and testing a classifier. Make sure all your labels are numeric, and the values are prepared for classification. Use 80% of the data points as training data.

1. Save german.data from https://archive.ics.uci.edu/ml/machine-learning-databases/statlog/german/, and open it in a text editor like Sublime Text or Atom. Add the following first row to it:

   CheckingAccountStatus DurationMonths CreditHistory CreditPurpose CreditAmount SavingsAccount EmploymentSince DisposableIncomePercent PersonalStatusSex OtherDebtors PresentResidenceMonths Property Age OtherInstallmentPlans Housing NumberOfExistingCreditsInBank Job LiabilityNumberOfPeople Phone ForeignWorker CreditScore

2. Import the data...