You customer wants to segment their customers1 demographic data into those that use and do not use loyalty card. What would you recommend?

Question

Options

• AUse Oracle OLAP Option.
• BUse Oracle SQL Analytic Functions.
• CUse classification algorithm in Oracle Data Mining.
• DUse non-negative matrix factorization in Oracle Data Mining.

• A
  7% (3)
• B
  2% (1)
• C
  9% (4)
• D
  82% (36)

Explanation

Classification is a data mining function that assigns items in a collection to target categories or classes. The goal of classification is to accurately predict the target class for each case in the For example, a classification model could be used to identify loan applicants as low, medium, or high credit risks. The simplest type of classification problem is binary classification. In binary classification, the target attribute has only two possible values: for example, high credit rating or low credit rating Oracle Data Mining provides the following algorithms for classification: Decision trees automatically generate rules, which are conditional statements that reveal the logic used to build the tree. Naive Bayes uses Bayes' Theorem, a formula that calculates a probability by counting the frequency of values and combinations of values in the historical data. * Generalized Linear Models (GLM) GLM is a popular statistical technique for linear modeling. Oracle Data Mining implements GLM for binary classification and for regression. GLM provides extensive coefficient statistics and model statistics, as well as row diagnostics. GLM also supports confidence bounds. * Support Vector Machine Support Vector Machine (SVM) is a powerful, state-of-the-art algorithm based on linear and nonlinear regression. Oracle Data Mining implements SVM for binary and multiclass

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