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Signed-off-by: pelinkeskin <[email protected]>

Time-Related_Feature_Engineering/README.md

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+### Building Time-Related Feature Engineering Pipelines with Python
+I built Time-Related Feature Engineering Pipelines with Python to predict [traffic volumes](https://archive.ics.uci.edu/ml/datasets/Metro+Interstate+Traffic+Volume ). I completed this project as part of an assignment in one of my modules during my Masters.  I performed time-related feature engineering by encoding time features using cyclic_spline_transformer and used wrapper strategy with sequential forward selection for feature selection. I built a predictive model using Stochastic Gradient Descent regression with polynomial transformation and achieved 85% accuracy in predicting traffic volumes.