Predictive and Specialized Modeling • Bootstrap Forest • Launch the Bootstrap Forest Platform • Launch Window
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Launch Window
Bootstrap Forest Launch Window
The Bootstrap Forest platform launch provides the following options:
Y, Response
The response variable or variables that you want to analyze.
X, Factor
The predictor variables.
Weight
A column whose numeric values assign a weight to each row in the analysis.
Freq
A column whose numeric values assign a frequency to each row in the analysis.
Validation
A numeric column that contains at most three distinct values. See Validation in Partition Models.
By
A column or columns whose levels define separate analyses. For each level of the specified column, the corresponding rows are analyzed using the other variables that you have specified. The results are presented in separate reports. If more than one By variable is assigned, a separate report is produced for each possible combination of the levels of the By variables.
Method
Enables you to select the partition method (Decision Tree, Bootstrap Forest, Boosted Tree, K Nearest Neighbors, or Naive Bayes). These alternative methods, except for Decision Tree, are available in JMP Pro.
For more details on these methods, see Partition Models, Boosted Tree, K Nearest Neighbors, and Naive Bayes.
Validation Portion
The portion of the data to be used as the validation set. See Validation in Partition Models.
Informative Missing
If selected, enables missing value categorization for categorical predictors and informative treatment of missing values for continuous predictors. See Informative Missing in Partition Models.
Ordinal Restricts Order
If selected, restricts consideration of splits to those that preserve the ordering.

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Help created on 9/19/2017