diagPlot {HVT} | R Documentation |
Function to construct Diagnosis Plots for HVT Model
diagPlot(
hvt.results,
data,
level,
quant.err,
distance_metric = "L1_Norm",
error_metric = "max",
...
)
hvt.results |
A list of hvt.results obtained from HVT function while performing hierarchical vector quantization on train data |
data |
Data frame. A data frame with different columns is given as input. The dataframe should be the same dataframe used to train the HVT Model |
level |
Numeric. Indicating the level for which the heat map is to be plotted. |
quant.err |
Numeric. A number indicating the quantization error threshold. |
... |
The ellipsis is passed to it as additional argument. (Used internally) |
This function creates Diagnosis Plots for HVT Model. The output of the functions contains a Minimum Intra-Centroid distance plot, a Minimum Intra-DataPoint Distance Plot, Distribution of number of cells, a Minimum Intra-DataPoint Distance Plot, Distribution of number of cells and count of singletons(segments with single observation)
A list that contains a Minimum Inter-Centroid distance plot, a Minimum Intra-DataPoint Distance Plot, Distribution of number of cells and count of singletons(segments with single observation)
cent_plot |
Plot. a Minimum Intra-Centroid distance plot |
datapoint_plot |
Plot. a Minimum Intra-Datapoints distance plot |
number_plot |
Plot. a Distribution of number of cells |
singleton_count |
Numeric. Count of singletons(segments with single observation) |
Shubhra Prakash <shubhra.prakash@mu-sigma.com>
data(USArrests)
hvt.results <- list()
hvt.results <- HVT(USArrests, n_cells = 15, depth = 1, quant.err = 0.2,
distance_metric = "L1_Norm", error_metric = "mean",
projection.scale = 10, normalize = TRUE,
quant_method="kmeans",diagnose=TRUE)
diagPlot(hvt.results = hvt.results,
data = USArrests,
level = 1,
quant.err = 0.2)