Boosted Tree

Example 1

Summary: Build a boosted tree model

Code:

// Open data table
dt = Open("$Sample_Data/Bands Data.jmp");
// Boosted Tree of Banding?
Random Reset( 123 );
Boosted Tree(
    Y( :Banding? ),
    X(
        :grain screened,
        :proof on ctd ink, :blade mfg,
        :paper type, :ink type,
        :direct steam, :solvent type,
        :type on cylinder, :press type,
        :unit number, :cylinder size,
        :paper mill location,
        :plating tank, :proof cut,
        :viscosity, :caliper,
        :ink temperature, :humidity,
        :roughness, :blade pressure,
        :varnish pct, :press speed,
        :ink pct, :solvent pct,
        :ESA Voltage, :ESA Amperage, :wax,
        :hardener, :roller durometer,
        :current density,
        :anode space ratio,
        :chrome content
    ),
    Validation Portion( 0.2 ),
    Method( "Boosted Tree" ),
    Splits per Tree( 3 ),
    Number of Layers( 41 ),
    Learning Rate( 0.1 ),
    Go
);

Example 2

Summary: Generate a boosted tree model with validation

Code:

// Open data table
dt = Open("$Sample_Data/Body Fat.jmp");
// Boosted Tree
Boosted Tree(
    Y( :Percent body fat ),
    X(
        :"Age (years)"n, :"Weight (lbs)"n,
        :"Height (inches)"n,
        :"Neck circumference (cm)"n,
        :"Chest circumference (cm)"n,
        :"Abdomen circumference (cm)"n,
        :"Hip circumference (cm)"n,
        :"Thigh circumference (cm)"n,
        :"Knee circumference (cm)"n,
        :"Ankle circumference (cm)"n,
        :
        "Biceps (extended) circumference (cm)"n,
        :"Forearm circumference (cm)"n,
        :"Wrist circumference (cm)"n
    ),
    Validation( :Validation ),
    Method( "Boosted Tree" ),
    Splits per Tree( 3 ),
    Number of Layers( 30 ),
    Learning Rate( 0.1 ),
    Go
);