NMF Compatibility Fix

Problem

The NMFRiskDiscovery class initialization failed with:

TypeError: NMF.__init__() got an unexpected keyword argument 'alpha'

Root Cause

The scikit-learn NMF class has different parameter names across versions:

scikit-learn < 0.19: No regularization parameters
scikit-learn 0.19-0.24: Uses alpha and l1_ratio
scikit-learn >= 1.0: Uses alpha_W, alpha_H, and l1_ratio

The code was using the old alpha parameter which doesn't exist in newer versions.

Solution

Implemented version detection to use the correct parameters:

import sklearn
sklearn_version = tuple(map(int, sklearn.__version__.split('.')[:2]))

nmf_params = {
    'n_components': n_components,
    'random_state': random_state,
    'init': 'nndsvda',
    'max_iter': 500
}

# Add regularization params if supported
if sklearn_version >= (1, 0):
    # scikit-learn >= 1.0
    nmf_params['alpha_W'] = 0.1
    nmf_params['alpha_H'] = 0.1
    nmf_params['l1_ratio'] = 0.5
elif sklearn_version >= (0, 19):
    # scikit-learn 0.19 to 0.24
    nmf_params['alpha'] = 0.1
    nmf_params['l1_ratio'] = 0.5
# else: very old version, use basic params only

self.nmf_model = NMF(**nmf_params)

Testing

Run the comparison script again:

python3 compare_risk_discovery.py --advanced

All 9 methods should now work correctly across different scikit-learn versions.

Files Modified

risk_discovery_alternatives.py: Fixed NMFRiskDiscovery.__init__() method