Feature engineering is an important area in the field of machine learning and data analysis. It helps in data cleaning process where data scientists and analysts spend most of their time on.
Here are few examples of feature engineering techniques
1.Outlier detection and removal
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Domain Knowledge
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Visualization ( BoxPlot - Scatter Plot etc .)
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Math/Statistics ( Percentile - Z Score - 2 standard deviation ) 2.One hot encoding
3.Log transform
4.Dimensionality reduction using principal component analysis (a.k.a. PCA)
5.Handling missing values
6.Scaling