ccosine | R Documentation |
This function takes a dataframe and a variable or variables (two or more) in input, and returns a matrix or matrices (two or more) with the Cosine dissimilarities about the factors inside them. You can also select "index" to calculate the Cosine dissimilarities between each row.
ccosine(
dataset,
formula,
plot = TRUE,
plot_title = "Cosine Dissimilarity Between Groups",
min_group_size = 3
)
dataset |
A dataframe. |
formula |
The index of the dataframe, otherwise a variable or variables (two or more) with factors which you want to calculate the Cosine dissimilarities matrix or matrices (two or more). |
plot |
Logical, if TRUE, a plot or plots (two or more) of the Cosine dissimilarities matrix or matrices about factors (two or more) are displayed. |
plot_title |
If plot is TRUE, the title to be used for plot or plots about factors. The default value is TRUE. |
min_group_size |
Minimum group size to maintain. The default value is 3, therefore groups, inside variables, with less than 3 observations will be discarded. For "index", this value is always 1. |
According to the option chosen in formula, with "index" the Cosine dissimilarities matrix will be printed; instead, by specifying variables, the Cosine dissimilarities matrix or matrices (two or more) between each pair of groups and, optionally, the plot or plots (two or more) will be printed.
If "index" is selected with variables, only dissimilarities between rows are calculated. Therefore, this snippet: "ccosine(mtcars, ~am + carb + index)" will print dissimilarities only considering "index". Rows with NA values are omitted.
# Example with iris dataset
data(iris)
ccosine(iris, ~Species, plot = TRUE,
plot_title = "Cosine Dissimilarity Between Groups")
# Example with mtcars dataset
data(mtcars)
ccosine(mtcars, ~am, plot = TRUE,
plot_title = "Cosine Dissimilarity Between Groups")
# Calculate the Cosine dissimilarity for 32 car models in "mtcars" dataset
res <- ccosine(mtcars, ~index)
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