HVT (version 24.9.1)

madPlot: Mean Absolute Deviation Plot

Description

Function to create Mean Absolute Deviation Plot

Usage

madPlot(hvt.scoring, ...)

Value

Mean Absolute Deviation Plot

mad_plot

ggplot plot. A plot with percentage anomalies on y axis and mean absolute deviation values on xaxis.

Arguments

hvt.scoring

List. A list of hvt.scoring obtained from the scoreHVT function.

...

The ellipsis is passed to it as additional argument. (Used internally)

Author

Shubhra Prakash <[e-mail]>

Details

This function plots percentage anomalies vs mean absolute deviation for test data. The plot helps in deciding an optimal MAD value for the use case.

See Also

scoreHVT

Examples

data("EuStockMarkets")
dataset <- data.frame(date = as.numeric(time(EuStockMarkets)),
                     DAX = EuStockMarkets[, "DAX"],
                     SMI = EuStockMarkets[, "SMI"],
                     CAC = EuStockMarkets[, "CAC"],
                     FTSE = EuStockMarkets[, "FTSE"])
#adding this step especially for this function
rownames(EuStockMarkets) <- dataset$date
train <- EuStockMarkets[1:1302, ]
test <- EuStockMarkets[1303:1860, ]
hvt_summary <- list()
hvt_summary<- trainHVT(train,n_cells = 15, depth = 1, quant.err = 0.2,
                      distance_metric = "L1_Norm", error_metric = "mean", 
                      normalize = TRUE, quant_method = "kmeans")
score_var <- scoreHVT(test, hvt_summary, child.level = 2, mad.threshold = 0.2)
madPlot(hvt.scoring=score_var)