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.
When fitting mixed features on a training set and trying to predict a testing set, the model through a ValueError indicates that operands could not be broadcast together with shapes that are different.
When fitting mixed features on a training set and trying to predict a testing set, the model through a ValueError indicates that operands could not be broadcast together with shapes that are different.
How to reproduce the error?
What is expected? model.predict should cluster the testing dataset giving a shape of (20,)
What actually happens?