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Oracle Data Mining provides the following algorithms for classification:
Decision Tree
Decision Tree automatically generates rules, which are conditional statements that reveal the logic used to build the tree.
Naive Bayes
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)
Generalized Linear Models 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, which are the upper and lower boundaries of an interval in which the predicted value is likely to lie.
Support Vector Machine (SVM)
Support Vector Machine is a powerful, state-of-the-art algorithm based on linear and nonlinear regression. Oracle Data Mining implements SVM for binary and multiclass classification.
Oracle Data Mining implements SVM for binary and multiclass classification.