Creates a standard discriminant function analysis, and computes various classification statistics. For best-subset selection of predictor effects in ANCOVA-like designs, see the General Discriminant Function Analysis (GDA) facilities.
General
Element Name
Description
Missing data deletion
Missing data can be deleted casewise or substituted by the respective predictor means.
A priori class. probabilities
Specifies how to compute a priori classification probabilities; a priori classification probabilities can either be computed proportional to the observed class (group) sizes or they can be the same for all groups.
Generates data source, if N for input less than
Generates a data source for further analyses with other Data Miner nodes if the input data source has fewer than k observations, as specified in this edit field; note that parameter k (number of observations) will be evaluated against the number of observations in the input data source, not the number of valid or selected observations.
Canonical Analysis
Element Name
Description
Canonical analysis
Performs canonical analysis; Statistica will compute Chi-square tests of successive canonical roots, and optionally compute the canonical scores for each case (observation).
Creates canonical scores
Creates scores for each case (observation) for each canonical variate.
Classification
Element Name
Description
Classification statistics
Creates classification summaries.
Creates posterior p
Creates posterior classification probabilities for each case (observation) and for each class.
Creates Mahalanobis d
Creates Mahalanobis distances for each case (observation) and for each class.
Creates predicted class
Creates predicted classifications (best, second best, ....).
