Analyze The Full Dataset

Lesson 13 of 17

So, to recap: we designed the data transformation pipeline specifically for a dataset of 10,000 trips, covering the early morning of December 1st, 2018. We made many assumptions based off the histograms, correlation matrix and scatterplot grid and baked those assumptions into the design of the machine learning pipeline.

Then we loaded the parquet dataset that covers the full month of December. The regression metrics of the full dataset are considerably worse than the ones for the limited set. This might be because the model was overfitting on the small dataset, or it could be because we now need to alter the data transformations to better match the new patters in the data.

We won’t know for sure until we recalculate the histograms, the correlation matrix and the scatterplots.

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