Boosted Model Tool

The Boosted Model tool creates generalized boosted regression models based on Gradient Boosting methods. The models are created by serially adding simple decision tree models to a model ensemble to minimize an appropriate loss function. These models use a method of statistical learning that:

  • self-determines which subset of fields best predicts a target field.
  • is able to capture non-linear relationships and interactions between fields.
  • can automatically address a broad range of regression and classification problems.

Use the Boosted Model tool for classification, count data, and continuous target regression problems.

This tool uses the R programming language. Go to Options > Download Predictive Tools to install R and the packages used by the R Tool.