ISSUE 1:
Currently when running
glrm, labels = GLRM(df, k)
on a dataset 'df' which has categorical variables, the GLRM is run ignoring these variables. The only way to figure out that this is happening from the User's end is checking length(labels).
DESIRED BEHAVIOR:
A warning message informing the user that variables in df are being ignored and suggesting the use of the expand_categoricals( ) function.
ISSUE 2:
Currently when running
df2 = expand_categoricals(df, v)
where df is a DataFrame and v is a vector with column indices, the command returns a Match error. It runs only after I run
v = convert(Array, v)
DESIRED BEHAVIOR:
Automatically converting the column indices vector to Array/ accepting vectors into the expand_categoricals( ) function.
ISSUE 1: Currently when running glrm, labels = GLRM(df, k) on a dataset 'df' which has categorical variables, the GLRM is run ignoring these variables. The only way to figure out that this is happening from the User's end is checking length(labels).
DESIRED BEHAVIOR: A warning message informing the user that variables in df are being ignored and suggesting the use of the expand_categoricals( ) function.
ISSUE 2: Currently when running df2 = expand_categoricals(df, v) where df is a DataFrame and v is a vector with column indices, the command returns a Match error. It runs only after I run v = convert(Array, v)
DESIRED BEHAVIOR: Automatically converting the column indices vector to Array/ accepting vectors into the expand_categoricals( ) function.