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Session 16: B/I - Multivariate Feature Engineering: Beyond Simple Data Preparation

Session 16: B/I - Multivariate Feature Engineering: Beyond Simple Data Preparation Basic feature engineering uses input data to create dummy variables, log transforms, and other single-value ...
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Description: Basic feature engineering uses input data to create dummy variables, log transforms, and other single-value transformations. This talk builds upon these univariate transformations and presents several strategies for creating complex multivariate features that can enhance your model's lift. Topics such as target encoding, dimension reduction/projection, row/column, and other feature engineering topics will be covered.
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- Authors: Jeff T Heaton, Qichun Xu
- Date: Sep 2019
- Competency: Technical Skills & Analytical Problem Solving
- Topics: Modeling & Statistical Methods>Data mining

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Session 16: B/I - Multivariate Feature Engineering: Beyond Simple Data Preparation