Target Polish: How to Polish Data and Reveal Its True Structure
Imagine you’re analyzing sensor data. Suddenly one sensor shows -999°C. That’s an outlier — a single data point that can completely ruin your analysis. 🧩 What is factorization? Matrix factorization means decomposing data $X$ into two non-negative components: $$ X \approx WH $$ Where $W$ contains “features” and $H$ shows how much of each is needed. 💡 The problem Classical methods like NMF are sensitive to noise and outliers. When data is messy, analysis breaks down. ...