TD_NonLinearCombineFit Function | NonLinearCombineFit - TD_NonLinearCombineFit - Analytics Database

Database Analytic Functions

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Analytics Database
Release Number
17.20
Published
June 2022
Language
English (United States)
Last Update
2024-04-06
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Product Category
Teradata Vantageā„¢

TD_NonLinearCombineFit function returns the target columns and a specified formula which uses the non-linear combination of existing features.

Feature engineering is the process of creating features from existing data to improve the performance of a machine learning model. One approach to feature engineering is to use a technique that combines existing features in a non-linear way to create ones that capture more complex relationships between the original features and the target.

By combining features in a non-linear way, this technique can create features that are not explicitly present in the original dataset. These features can help to simplify the model, reduce overfitting, and improve the interpretability of the model. Moreover, this technique can help to identify the most relevant features by evaluating the performance of the model with different combinations of the original features and their non-linear combinations.

In summary, feature engineering with non-linear combinations of features is an important technique for improving the performance and interpretability of machine learning models. This can help to create features, simplify the model, reduce overfitting, and identify the most relevant features for the target.