I have a dataset containing insurance Claims with quantitative and qualitative variables but PCA refuses to convert or work with "string" type variables.
This is the code I used :
from sklearn.decomposition import PCA claims=pd.read_csv('./insurance_claims.csv',sep=',',header=0) X=claims.ix[:,1:].values pca=PCA(n_components=12) pca.fit(X)
I'm trying to reduce dimensionality to cluster the dataset and detect fraudulous claims. If there is any alternative to PCA for heterogenous data much appreciated.