Extract structural/shape information.
Convert text into numerical importance scores. 75bdb.7z
If you can describe the contents or provide a few rows of data, I can give you a specific feature engineering plan. In the meantime, here are common feature generation strategies based on the likely type of data: 1. If it contains Tabular Data (CSV/Excel) Extract structural/shape information
Use a library like TextBlob or VADER to generate a numerical "mood" for the text. 4. If it contains Image Data Color Histograms: Quantify the distribution of colors. 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.
Replace categorical levels with the mean of the target variable.