Tree-Based Classification Tools

Decision Tree, Random Forest and XGBoost

Build tree-based classification models using training data, cross-validation, random split validation and optional external validation data.

Training data

Use first row as variable names

Use first column as sample IDs

External validation data (optional)

External data includes known class/group in last column

Data normalization

Number of trees

Maximum tree depth

Split criterion

Validation mode