Discriminant AnalysisDiscriminant analysis predicts membership of each document in a group or category based on the columns in the document term matrix (DTM). Specifically, discriminant analysis predicts a classification of each document into a category of a response column. When you select the Discriminant Analysis option, you must select a response column that contains categories or groups. Group membership is predicted by the columns of the DTM. For more information about discriminant analysis, see Discriminant Analysis in the Multivariate Methods book.
Discriminant Analysis Specifications WindowThe weighting scheme that determines the values that go into the cells of the document term matrix. The weighting scheme options are described in Document Term Matrix Specifications Window.
Discriminant Analysis ReportProvides a table that contains the squared Mahalanobis distances to each group for each document. For more information about Mahalanobis distances, see Outlier Analysis in the Multivariate Methods book.
Discriminant Analysis Report OptionsEach probability column gives the posterior probability of an observation’s membership in that level of the response. The Response Probability column property is saved to each probability column. For more information about the Response Probability column property, see Column Properties in the Using JMP book.
Saves formula columns to the data table for the prediction of the most likely response. The first saved column contains a formula that uses the Text Score() function to calculate the probability for each response level. There are also columns that contain probabilities for each response level as well as a column that contains the predicted response.