NMF

NMF (Non-negative Matrix Factorisation) is a dimensionality reduction technique available through scikit-learn, a free Python machine learning library. It breaks down large, complex datasets into simpler components by factorising matrices into non-negative factors. This approach works well when your data is naturally non-negative, such as image pixels, word counts, or audio spectrograms. NMF helps you identify hidden patterns and relationships that aren't immediately obvious in raw data. It's particularly useful for feature extraction, topic modelling, and data compression. Unlike some other decomposition methods, NMF produces interpretable results because negative values aren't allowed, making the discovered patterns easier to explain to stakeholders. Data scientists and machine learning practitioners use it to reduce computational load, improve model performance, and gain insight into what their data actually contains.