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1
Why did you use One-Hot Encoding instead of Label Encoding?
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2
For every preprocessing step: Why this technique and not another one?
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3
Why did you choose each hyperparameter in your model?
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4
Why did you use eval_metric='logloss'?
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5
Why did you choose a particular threshold value?
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6
Is Pickup Location ID useful? Why?
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7
Is Drop Location ID useful? Why?
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8
What do you observe about the target variable?
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9
Why do you say the target variable is normally distributed?
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10
Explain the advantages and disadvantages of each model you used compared to the others.
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11
Show graphs during EDA.
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12
Explain every graph and why you plotted it.
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13
Plot a graph comparing y_pred vs y_test (or prediction error) for every model.