Support Vector Machines Platform Options
The Support Vector Machine red triangle menu contains the following options:
See Local Data Filters in JMP Reports, Redo Menus in JMP Reports, Group Platform, and Save Script Menus in JMP Reports in Using JMP for more information about the following options:
Local Data Filter
Shows or hides the local data filter that enables you to filter the data used in a specific report.
Redo
Contains options that enable you to repeat or relaunch the analysis. In platforms that support the feature, the Automatic Recalc option immediately reflects the changes that you make to the data table in the corresponding report window.
Platform Preferences
Contains options that enable you to view the current platform preferences or update the platform preferences to match the settings in the current JMP report.
Save Script
Contains options that enable you to save a script that reproduces the report to several destinations.
Save By-Group Script
Contains options that enable you to save a script that reproduces the platform report for all levels of a By variable to several destinations. Available only when a By variable is specified in the launch window.
Note: Additional options for this platform are available through scripting. Open the Scripting Index under the Help menu. In the Scripting Index, you can also find examples for scripting the options that are described in this section.
Support Vector Machine Model Report Options
Each Support Vector Machine Model report contains the following options:
Response Profile Plot
(Available only if the response is categorical.) Shows or hides the Response Profile Plot.
Support Vector Coefficients
Shows or hides the table of support vector coefficients. Select rows in the table to highlight the support vectors in the original data table and the Response Profile Plot.
Confusion Matrix
(Available only if the response is categorical.) Shows or hides the confusion matrix. See Confusion Matrix.
ROC Curve
(Available only if the response is categorical.) Shows or hides the Receiver Operating Characteristic (ROC) plot that contains a curve for each level of the response variable. If you used validation, a plot is shown for each of the training, validation, and test sets. See ROC Curve.
Precision Recall Curve
(Available only for categorical responses.) Shows or hides the Precision-Recall Curve plot that contains a curve for each level of the response variable. A precision-recall curve plots the precision values against the recall values at a variety of thresholds. If you used validation, a plot is shown for each of the training, validation, and test sets. See Precision-Recall Curve.
Lift Curve
(Available only if the response is categorical.) Shows or hides the Lift Curve. If you used validation, a plot is shown for each of the training, validation, and test sets. See Lift Curve.
Plot Actual by Predicted
(Available only if the response is continuous.) Shows or hides a plot of the actual values versus the predicted values.
Plot Residual by Predicted
(Available only if the response is continuous.) Show or hides a plot of the residuals versus the predicted values.
Profiler
Shows or hides the Prediction Profiler. Each response level is represented by a separate row in the Prediction Profiler. For more information about the options in the red triangle menu, see Prediction Profiler Options in Profilers.
Contour Profiler
(Available only when the model contains more than one continuous factor.) Shows or hides the Contour Profiler. For more information about the options in the red triangle menu, see Contour Profiler Platform Options in Profilers.
Surface Profiler
(Available only when the model contains at least one continuous factor.) Shows or hides a surface profiler. For more information about the options in the red triangle menu, see Surface Plot Platform Options in Profilers.
Save Predicteds
Saves the predicted classifications based on the threshold probability cutoff value to the data table in a column called Predicted <Y, Response>.
Save Prediction Formula
Saves the prediction formulas based on the threshold probability cutoff value to the data table. If the response is binary, a single prediction formula column is added to the data table. If the response has more than two levels, a prediction formula column is added to the data table for each pairwise model, in addition to a formula column for the final prediction.
Publish Prediction Formula
Creates probability formulas based on the threshold probability cutoff value and saves them as formula column scripts in the Formula Depot platform. If a Formula Depot report is not open, this option opens the Formula Depot window. See Formula Depot.
Save Probabilities
Saves the probability of each response level as a separate column in the data table, as well as a column called Most Likely <Y, Response>.
Save Probability Formula
(Available only if the response is binary.) Saves the following formula columns to the data table:
Decision Value
A hidden column that contains the formula for the decision value.
Probability
Two probability formula columns, one for each level of the binary response.
Most Likely
The predicted classification based on which probability value is higher.
Threshold Predicted
The predicted classification based on the threshold probability cutoff value obtained from the confusion matrix. By default, this value is based on the classification decision rule that is calculated by the platform. If the threshold value is changed to 0.5, the Threshold Predicted column is not saved to the data table because it would be equivalent to the Most Likely column.
Publish Probability Formula
(Available only if the response is binary.) Creates probability formulas and saves them as formula column scripts in the Formula Depot platform. If a Formula Depot report is not open, this option opens the Formula Depot window. See Formula Depot.
Save Validation
(Available only when the Holdback or KFold validation methods are used.) Creates a new column in the data table that identifies which rows were used in the training and validation sets.
Remove Fit
Removes the entire model report.