Confirm that the selected features are not just clear and concise but actually effective for decision-making.

: Identify the specific outcome (e.g., land type in hyperspectral imaging or fraud in financial transactions).

: In specialized fields, this involves searching for key classifying features within a specific area that characterize its unique properties. 3. Feature Selection (Iterative Process)

Convert raw, unstructured data into a numerical format that a model can process.

: Add one additional feature to your selected set and re-test. Keep the addition if accuracy improves significantly.

: If substantial revision is required, re-examine the extraction step to create more complex "engineered" features.