A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
categorical_nan fails with the following traceback
499 # Get maximal number of outcomes
500 if max_n_outcomes is None:
--> 501 max_n_outcomes = int(array.max() + 1)
502
503 # Create one-hot encoding
ValueError: cannot convert float NaN to integer```
categorical_nanfails with the following traceback