Specification Window | JMP 13.2

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Predictive and Specialized Modeling • Bootstrap Forest • Launch the Bootstrap Forest Platform • Specification Window

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Specification Window

After you select OK in the launch window, the Bootstrap Forest Specification window appears.

Bootstrap Forest Specification Window

Specification Panel

The number of rows in the data table.

Number of Terms

The number of columns that are specified as predictors.

Forest Panel

Number of Trees in the Forest

Number of trees to grow and then average.

Number of Terms Sampled per Split

Number of predictors to consider as splitting candidates at each split. For each split, a new random sample of predictors is taken as the candidate set.

Bootstrap Sample Rate

Proportion of observations to sample (with replacement) for growing each tree. A new random sample is generated for each tree.

Minimum Splits Per Tree

Minimum number of splits for each tree.

Maximum Splits Per Tree

Maximum number of splits for each tree.

Minimum Size Split

Minimum number of observations needed on a candidate split.

(Available only if validation is used.) If selected, the process stops growing additional trees if adding more trees does not improve the validation statistic. The validation statistic is the validation set’s Entropy RSquare value for a categorical response and its RSquare value for a continuous response. If not selected, the process continues until the specified number of trees is reached.

Multiple Fits Panel

Multiple Fits over Number of Terms

If selected, creates a bootstrap forest for several values of number of terms sampled per split. The model for which results are displayed is the model whose Validation Set’s Entropy RSquare value (for a categorical response) or RSquare (for a continuous response) is the largest.

The lower bound is the Number of Terms Sampled per Split specification. The upper bound is specified by the following option:

Max Number of Terms

The maximum number of terms to consider for a split.

Use Tuning Table Design

Opens a window where you can select a data table containing values for the Forest panel tuning parameters, called a tuning design table. A tuning design table has a column for each option that you want to specify and has one or multiple rows that each represent a single Bootstrap Forest model design. If an option is not specified in the tuning design table, the default value is used.

For each row in the table, JMP creates a Bootstrap Forest model using the tuning parameters specified. If more than one model is specified in the tuning design table, the Model Validation-Set Summaries report lists the RSquare value for each model. The Bootstrap Forest report shows the fit statistics for the model with the largest RSquare value.

You can create a tuning design table using the Design of Experiments facilities. A bootstrap forest tuning design table can contain the following case-insensitive columns in any order:

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Portion Bootstrap

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Minimum Splits per Tree

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Maximum Splits per Tree

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Minimum Size Split

Reproducibility Panel

Suppress Multithreading

If selected, all calculations are performed on a single thread.

Specify a nonzero numeric random seed to reproduce the results for future launches of the platform. By default, the Random Seed is set to zero, which does not produce reproducible results. When you save the analysis to a script, the random seed that you enter is saved to the script.

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Help created on 9/19/2017