Calculate the moving average or standard deviation over a specific window.
Capture sequences of words (bigrams or trigrams) to maintain context. 75bdb.7z
Create new features by multiplying or dividing existing numerical columns (e.g., Price * Quantity ). Polynomial Features: Generate x2x squared for non-linear relationships. Calculate the moving average or standard deviation over
Convert continuous numerical data into discrete categories (e.g., "Low", "Medium", "High"). 2. If it contains Time-Series Data Lag Features: Include values from previous time steps ( 75bdb.7z
If you provide the column names or a summary, I can generate specific Python code for you.
Pass images through a pre-trained model (like ResNet) to get high-level feature vectors.