Standard Discriminant Analysis
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.
Element Name | Description |
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General | |
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 | |
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 | |
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, ....). |
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