Boosted Trees Specifications - Classification Tab
Select the Classification tab of the Boosted Trees Specifications dialog box to access two group boxes: Misclassification costs and Prior probabilities. Use the options in these group boxes to choose the misclassification cost (Equal or User spec.) and the prior probabilities (Estimated, Equal, or User specified) for the Boosting Trees analysis. Note that these options are available only if the dependent (criterion) variable in the current analysis is categorical, i.e., if Classification analysis was selected as the Type of analysis on the Boosted Trees Startup Panel - Quick tab ( i.e., if the goal of the current analysis is to correctly classify cases (observations) into the groups specified in the dependent variable; also, in order to specify user-defined priors, you first have to select the specific dependent variables codes defining the number and names of classes in the analysis).
- Misclassification costs
- Use the options in this group box to assign greater importance to the accurate prediction (classification) for some classes as compared to others. For example, in medical research you may want assign greater importance to the accurate classification of malignant tumors as compared to accurate discrimination between different types of benign forms. In this case, you would assign greater costs to the misclassification of malignant tumors, and lower costs to the misclassification of benign tumors. Note also that, as illustrated in this example, the matrix of misclassification costs does not necessarily have to be symmetric, and in fact it rarely is (i.e., it is more costly to misclassify malignant tumors as benign, than the other way around).
The misclassification costs are combined with the prior probabilities when computing the classification probabilities (during estimation, as well as when computing the final classification probabilities); for details regarding these computations see Friedman (1999a, p. 11; essentially, the cost will be applied as a relative weight to the classification probabilities, and final classifications will be determined from the products of the two).
- Equal
- If you select the Equal option button, each off-diagonal element of the predicted class (row) by observed class (column) misclassification costs matrix is set equal to 1.0, and the specified prior probabilities for the classes on the dependent variable are not adjusted.
- User specified
- Select the User specified option button if more accurate classification is desired for some classes than others. Note that this option is available only if you have selected the dependent variable codes by clicking the Response codes button on the Quick tab. See also the description of these options in the Classification Trees module for more details.
- Prior probabilities
- Use the options in this group box to specify how likely it is, without using any prior knowledge of the values for the predictor variables in the model, that a case or object will fall into one of the classes. The Prior probabilities group box contains three options for this purpose: Estimated, Equal, and User specified. Note that the User specified option is available only after you have selected the specific Response codes for the dependent variable on the Quick tab of the Specification dialog.
The prior probabilities will be combined with the prediction probabilities and misclassification costs to compute the classification probabilities during the estimation (building of trees), and to compute the final classifications (see also, Computational Details).
- Estimated
- Select the Estimated option button to specify that the likelihood that a case or object will fall into one of the classes is proportional to the dependent variable class sizes. See also the description of this option for the Classification Trees Analysis module for additional details.
- Equal
- Select the Equal option button to specify that the likelihood that a case or object will fall into one of the classes is the same for all dependent variable classes. See also the description of this option for the Classification Trees Analysis module for more details.
- User specified
- Select the User specified option button if you have specific knowledge about the base rates (for example, based on previous research). When you select the User specified option button, the Enter values for the prior probabilities dialog box will be displayed, in which you can specify the a priori probabilities for each class of the dependent variable. This dialog box is automatically displayed only the first time that priors are set to user-defined (i.e., the first time the User specified option button is selected); thereafter, click the accompanying settings button to display the dialog box containing the previously specified values. If the probabilities do not add up to 1.0, Statistica will automatically adjust them proportionately.