Glossary

Feature engineering

Feature engineering:

In predictive modeling, a key step is to turn available data (which may come from varied sources and be messy) into an orderly matrix of rows (records to be predicted) and columns (predictor variables or features). The feature engineering process involves review of the data by a domain expert to provide an initial estimate of what will be useful. Data cleanup, exploration of the data for correlations, data reduction, and handling of missing data are also part of the feature engineering process.

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