clusterICE function

Clustering of ICE and d-ICE curves by kmeans.

Clustering if ICE and d-ICE curves by kmeans. All curves are centered to have mean 0 and then kmeans is applied to the curves with the specified number of clusters.

clusterICE(ice_obj, nClusters, plot = TRUE, plot_margin = 0.05, 
           colorvec, plot_pdp = FALSE, x_quantile = FALSE, 
           avg_lwd = 3, centered = FALSE, 
           plot_legend = FALSE, ...)

Arguments

• ice_obj: Object of class ice or dice to cluster.
• nClusters: Number of clusters to find.
• plot: If TRUE, plots the clusters.
• plot_margin: Extra margin to pass to ylim as a fraction of the range of cluster centers.
• colorvec: Optional vector of colors to use for each cluster.
• plot_pdp: If TRUE, the PDP (ice object) or d-PDP (dice object) is plotted with a dotted black line and highlighted in yellow.
• x_quantile: If TRUE, the plot is drawn with the x-axis taken to be quantile(gridpts). If FALSE, the predictor's original scale is used.
• avg_lwd: Average line width to use when plotting the cluster means. Line width is proportional to the cluster's size.
• centered: If TRUE, all cluster means are shifted to be to be 0 at the minimum value of the predictor. If FALSE, the original cluster means are used.
• plot_legend: If TRUE a legend mapping line colors to the proportion of the data in each cluster is added to the plot.
• ...: Additional arguments for plotting.

Returns

The ouput of the kmeans call (a list of class kmeans).

See Also

ice, dice

Examples

## Not run:

require(ICEbox)
require(randomForest)
require(MASS) #has Boston Housing data, Pima

data(Boston) #Boston Housing data
X = Boston
y = X$medv
X$medv = NULL

## build a RF:
bh_rf = randomForest(X, y)

## Create an 'ice' object for the predictor "age":
bh.ice = ice(object = bh_rf, X = X, y = y, predictor = "age",
            frac_to_build = .1) 

## cluster the curves into 2 groups.
clusterICE(bh.ice, nClusters = 2, plot_legend = TRUE)

## cluster the curves into 3 groups, start all at 0.
clusterICE(bh.ice, nClusters = 3, plot_legend = TRUE, center = TRUE)
## End(Not run)