Weights are being normalized using number of samples as opposed to sum in GaussianMixture #24085
Closed as not planned
Description
Describe the bug
Weights are being normalized at Line https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/mixture/_gaussian_mixture.py#L718 using n_samples. It should be done using weights.sum() as
done in _m_step() here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/mixture/_gaussian_mixture.py#L756.
Steps/Code to Reproduce
Weights are being normalized at Line https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/mixture/_gaussian_mixture.py#L718 using n_samples. It should be done using weights.sum() as
done in _m_step() here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/mixture/_gaussian_mixture.py#L756.
Expected Results
Correct weights.
Actual Results
Incorrect weights.
Versions
System:
python: 3.9.13 (main, May 24 2022, 21:28:31) [Clang 13.1.6 (clang-1316.0.21.2)]
executable: /Users/kshitijgoel/Documents/main/code.nosync/self_organizing_gmm/.venv/bin/python
machine: macOS-12.4-x86_64-i386-64bit
Python dependencies:
sklearn: 1.1.1
pip: 22.2.1
setuptools: 62.3.2
numpy: 1.23.1
scipy: 1.8.1
Cython: 0.29.30
pandas: 1.4.3
matplotlib: 3.5.2
joblib: 1.1.0
threadpoolctl: 3.1.0
Built with OpenMP: False
threadpoolctl info:
user_api: blas
internal_api: openblas
prefix: libopenblas
filepath: /Users/kshitijgoel/Documents/main/code.nosync/self_organizing_gmm/.venv/lib/python3.9/site-packages/numpy/.dylibs/libopenblas64_.0.dylib
version: 0.3.20
threading_layer: pthreads
architecture: Haswell
num_threads: 8
user_api: blas
internal_api: openblas
prefix: libopenblas
filepath: /Users/kshitijgoel/Documents/main/code.nosync/self_organizing_gmm/.venv/lib/python3.9/site-packages/scipy/.dylibs/libopenblas.0.dylib
version: 0.3.17
threading_layer: pthreads
architecture: Haswell
num_threads: 8