Computes the extended Gower distance of two data sets
The function gowerD is used by kNN to compute the distances for numerical, factor ordered and semi-continous variables.
gowerD( data.x, data.y = data.x, weights = rep(1, ncol(data.x)), numerical = colnames(data.x), factors = vector(), orders = vector(), mixed = vector(), levOrders = vector(), mixed.constant = rep(0, length(mixed)), returnIndex = FALSE, nMin = 1L, returnMin = FALSE )
data.x |
data frame |
data.y |
data frame |
weights |
numeric vector providing weights for the observations in x |
numerical |
names of numerical variables |
factors |
names of factor variables |
orders |
names of ordered variables |
mixed |
names of mixed variables |
levOrders |
vector with number of levels for each orders variable |
mixed.constant |
vector with length equal to the number of semi-continuous variables specifying the point of the semi-continuous distribution with non-zero probability |
returnIndex |
logical if TRUE return the index of the minimum distance |
nMin |
integer number of values with smallest distance to be returned |
returnMin |
logical if the computed distances for the indices should be returned |
returnIndex=FALSE: a numerical matrix n x m with the computed distances returnIndex=TRUE: a named list with "ind" containing the requested indices and "mins" the computed distances
data(sleep) # all variables used as numerical gowerD(sleep) # split in numerical an gowerD(sleep, numerical = c("BodyWgt", "BrainWgt", "NonD", "Dream", "Sleep", "Span", "Gest"), orders = c("Pred","Exp","Danger"), levOrders = c(5,5,5)) # as before but only returning the index of the closest observation gowerD(sleep, numerical = c("BodyWgt", "BrainWgt", "NonD", "Dream", "Sleep", "Span", "Gest"), orders = c("Pred","Exp","Danger"), levOrders = c(5,5,5), returnIndex = TRUE)
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