plot_tree: Plot tree structure

In richardangell/GbmExplainR: Decompose gbm predictions into feature contributions + bias

Description

Plot structure for given tree in gbm, with the option to display the path to a terminal node for 1 row of data.

Usage

plot_tree(gbm, tree_no, plot_path = NULL)

Arguments

gbm	gbm.object to predict with.
tree_no	specific tree to plot from the model.
plot_path	single row data.frame to predict and the decompose into feature contributions. Default value NULL means not terminal node path will be displayed.

Value

function does not return anything but plots tree structure.

Examples

N <- 1000
X1 <- runif(N)
X2 <- 2*runif(N)
X3 <- ordered(sample(letters[1:4],N,replace=TRUE),levels=letters[4:1])
X4 <- factor(sample(letters[1:6],N,replace=TRUE))
X5 <- factor(sample(letters[1:3],N,replace=TRUE))
X6 <- 3*runif(N) 
mu <- c(-1,0,1,2)[as.numeric(X3)]

SNR <- 10 # signal-to-noise ratio
Y <- X1**1.5 + 2 * (X2**.5) + mu
sigma <- sqrt(var(Y)/SNR)
Y <- Y + rnorm(N,0,sigma)

# introduce some missing values
X1[sample(1:N,size=500)] <- NA
X4[sample(1:N,size=300)] <- NA

data <- data.frame(Y=Y,X1=X1,X2=X2,X3=X3,X4=X4,X5=X5,X6=X6)

# fit initial model
gbm1 <- gbm(Y~X1+X2+X3+X4+X5+X6,        
           data=data,                  
           var.monotone=c(0,0,0,0,0,0),
           distribution="gaussian",   
           n.trees=1000,     
           shrinkage=0.05,  
           interaction.depth=3,
           bag.fraction = 0.5,
           train.fraction = 0.5)

plot_tree(gbm1, 1, data[1, ])

richardangell/GbmExplainR documentation built on May 22, 2019, 12:54 p.m.