Workspace Node: Advanced Regression CHAID - Results - Quick Tab
In the Advanced Regression CHAID workspace node dialog box, under the Results heading, select the Quick tab to access the following options.
Manager.
Element Name | Description |
---|---|
Grow tree | Select this option button to automatically grow the tree, using all current settings. |
Grow tree 1 level | Select this option button to grow the tree one level down from each of the terminal nodes. Note that branches will only be grown if this is consistent with the current parameter settings for growing the tree (e.g., stopping rules as specified on the Specifications - Stopping tab). |
Tree View | Use the options in this group box to review the tree. In order to review all details of large trees with many terminal nodes, use the Tree browser option, which will create a reporting document where the nodes can be navigated using tree-browser facilities. |
Tree browser | Select this check box to produce a complete representation of the results tree in a browser, where every node is represented by a graph containing the respective split rule (unless the respective node is a terminal node) and various summary statistics. Intermediate and terminal nodes will be shown in the browser with different symbols:
This browser provides a complete summary of the results and enables you to efficiently review even the most complex trees (see also, for example, the General Classification and Regression Trees (GC&RT) topic Reviewing Large Trees: Unique Analysis Management Tools). The results displayed will differ depending upon whether the selected response variable is categorical or continuous. Click on a node in the tree browser to view a graph displaying the mean and variance of the variable as well as the plot of normal density with these parameters for the selected node. |
Tree graph | Select this check box to produce a Tree graph for the current tree. In this graph, each node will be presented as a rectangular box; the terminal nodes are highlighted in red, and the intermediate nodes are highlighted in blue (by default). The following information is usually summarized in this graph: Node ID, the node size, the selected category of the response and the histogram (for classification-type problems) or the mean and variance at the node (for regression-type problems). The graph also contains splitting information for the intermediate nodes - the splitting criterion that created its child nodes and the name of the predictor that was used in the splitting criterion. Note that all labels and legends for the graph are produced as custom text and can be edited, moved, or deleted via the Graph Options dialog box. |
Tree layout | Select this check box to produce a graph showing the structure of the current tree. Each node will be presented as a rectangular box; terminal nodes are highlighted in red and non-terminal nodes are highlighted in blue. |
Scrollable tree | Select this check box to produce a Tree graph in a scrollable window. |
Tree structure | Select this check box to create a Tree Structure spreadsheet, which contains summary information for all splits and the terminal nodes for the current tree. The information available in the tree structure will include for each node:
Additionally, the tree structure will contain information about the mean and variance of the dependent variable for the cases or objects belonging to the node. |
Terminal nodes | Select this check box to produce a spreadsheet containing summary information for the terminal nodes only.
For regression problems (continuous dependent variable), the spreadsheet shows the number of cases or objects in each observed class that are sent to the node, and the respective node mean and variance. |
Importance | Select the Importance check box with the spreadsheet icon to produce a spreadsheet that contains the importance ranking on a 0-100 scale for each predictor variable in the analysis. Computational details regarding this measure can be found in Breiman (1984; p. 147). In general, with the results presented in this spreadsheet, you can judge the relative importance of each predictor variable for producing the final tree. Refer to the discussion in Breiman (1984) for details. See also, Predictor Importance in Statistica GC&RT, Interactive Trees, and Boosted Trees. |
Importance | Select the Importance check box with the plot icon to produce a bar graph that pictorially shows the importance ranking on a 0-100 scale for each predictor variable considered in the analysis. This plot can be used for visual inspection of the relative importance of the predictor variables used in the analysis and, thus, helps to conclude which predictor variable is the most important predictor. See also, Predictor Importance in Statistica GC&RT, Interactive Trees, and Boosted Trees. |
Risk estimates | Select this check box to produce a spreadsheet with risk estimates for the analysis sample, the test sample (if one is specified on the
Specifications - Validation tab), and the v-fold cross-validation risk (if v-fold cross-validation is requested on the
Specifications -
Validation tab).
Options / C / W. See Common Options. |
OK | Click this button to accept all the specifications made in the dialog box and to close it. The analysis results are placed in the Reporting Documents workspace node after running (updating) the project. |