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Feature engineering involves creating new variables from existing data from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
Feature engineering is a critical step in the data preparation process. It involves creating new variables from existing data, which can help improve the performance of machine learning models. By transforming the raw data into new features, data scientists can capture more information and relationships that may not be apparent in the original dataset. This process requires a deep understanding of the domain and the data, as well as creativity and experimentation. There are many techniques that data scientists can use for feature engineering. One common approach is to create interaction terms by multiplying two or more variables together. This can help capture non-linear relationships between the ...
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