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Feature Engineering Techniques
An introduction to some of the main techniques which can be used in order to prepare raw features for Machine Learning analysis.
Published in
8 min readNov 15, 2019
Introduction
Feature Engineering is one of the most important steps to complete before starting a Machine Learning analysis. Creating the best possible Machine Learning/Deep Learning model can certainly help to achieve good results, but choosing the right features in the right format to feed in a model can by far boost performances leading to the following benefits:
- Enable us to achieve good model performances using simpler Machine Learning models.
- Using simpler Machine Learning models, increases the transparency of our model, therefore making easier for us to understand how is making its predictions.
- Reduced need to use Ensemble Learning techniques.
- Reduced need to perform Hyperparameters Optimization.