Feature Selection Analysis

Click the Summary button to compute the results; if no variables have been specified, the program will display the standard four-variable selection dialog box where you can select the dependent (outcome) and predictor variables for the analyses; both continuous and categorical dependent variables and predictors can be specified, and analyses will be performed for each dependent variable one at a time. See also the Feature Selection and Variable Screening Introductory Overview for additional details.

If variables have been selected, clicking the Summary button will begin the analyses and display the requested results. Use the options on the Advanced tab to select which results to compute. In general, the options available on this dialog are identical in terms of the results that can be computed to those available in the Feature Selection and Variable Screening module.

Click the Cancel button to close the dialog without performing an analysis.

Click the Options button to display the Options menu.

Click the Open Data button to display the Select Data Source dialog box, which is used to choose the spreadsheet on which to perform the analysis. The Select Data Source dialog box contains a list of the spreadsheets that are currently active.

Click the Select Cases button to display the Analysis/Graph Case Selection Conditions dialog box, which is used to create conditions for which cases will be included (or excluded) in the current analysis. More information is available in the Case Selection Conditions Overview, Case Selection Conditions Syntax Summary, and Case Selection Conditions dialog box description.

Click the W (Weight) button to display the Analysis/Graph Case Weights dialog box, which is used to adjust the contribution of individual cases to the outcome of the current analysis by "weighting" those cases in proportion to the values of a selected variable.

If the casewise deletion of missing data is selected, Statistica will ignore in the analyses all cases (observations) that have missing data for any of the variables selected for the analyses. Selecting casewise deletion of missing data may not be desirable when many predictor variables are specified, each with many missing data. In that case it can happen that practically all observations are excluded from the analyses. An alternative strategy is to first perform an initial feature (variable) selection without selecting this option, followed by a second analysis with casewise deletion of missing data for only those variables selected in the first pass.