Predictive and Specialized Modeling • Boosted Tree • Launch the Boosted Tree Platform

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Launch the Boosted Tree Platform
Launch the Boosted Tree platform by selecting Analyze > Predictive Modeling > Boosted Tree.
Figure 7.6 Boosted Tree Launch Window Using Body Fat.jmp
The Boosted Tree platform launch window has 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 about these methods, see Partition Models, Bootstrap Forest, K Nearest Neighbors, and NaiveBayes.
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 3/19/2020