Plots the PDP, ALE, or ICE plots for an Interpreter object
Usage
# S3 method for Interpreter
plot(
x,
method = "pdp+ice",
features = NULL,
features.2d = NULL,
clusters = NULL,
clusterType = "preds",
smooth = FALSE,
smooth.bandwidth = NULL,
smooth.kernel = "normal",
smooth.npoints = 2 * x$grid.size,
...
)Arguments
- x
Interpreter object to generate plots from
- method
The type of plot that we want to generate. Must be one of "ice", "pdp+ice", "pdp", or "ale"
- features
a vector of feature names that we want to produce 1-D plots for.
- features.2d
2-D features that we want to produce plots for arguments. A two-column dataframe of pairs of features to make local surrogates for. Each row represents a pair of features, with the names of features as the entries.If the 'method' parameter is set to "ale", this argument should not be used.
- clusters
A number of clusters to cluster the ICE predictions with. If this is not NULL, one must use the method "ice".
- clusterType
An indicator specifying what method to use for the clustering. The possible options are "preds", and "gradient". If "preds" is used, the clusters will be determined by running K means on the predictions of the ICE functions. If the "gradient" option is used, the clusters will be determined by running K means on the numerical gradient of the predictions of the ICE functions. If this is not NULL, one must use the method "ice".
- smooth
A binary variable to determine whether to smoothen the plots of the PDP, ICE, or ALE curves for continuous variables.
- smooth.bandwidth
The bandwidth for the kernels. They are scaled such that their quartiles are at 0.25 * bandwidth. By default, this is set as the maximum difference between the minimum and maximum of the grid points.
- smooth.kernel
The type of kernel to be used. Users can input either strings "box" or "normal". The default is "normal".
- smooth.npoints
The number of points returned when using the kernel method. By default, this is twice the number of grid points for that feature.
- ...
Additiional parameters to pass to the plot function
Value
A list of plots with 1-d features and 2-d features. For 2-d features with one continuous and one categorical feature, the plot is a linear plot of the continuous feature with group colors representing the categorical feature. For two continuous features, the plot is a heatmap with the shade representing the value of the outcome.