plot_feature_contributions: Plot feature contributions

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

Description

Plot a simple barchart of feature contributions for a given prediction.

Usage

plot_feature_contributions(feature_contributions)

Arguments

feature_contributions

feature contributions output from decompose_gbm_prediction, note this must be run with aggregate_contributions = TRUE.

Value

function does not return anything but plots barchart.

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)

preds_decomp <- decompose_gbm_prediction(gbm1, data[1, ])

plot_feature_contributions(preds_decomp)

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