Building predictive model for the use case

So far, we have defined the problem and designed the approach. We explored the data and studied the patterns across a variety of parameters captured through the sensors. We then engineered the data and created a couple of features that depict the day-level activities in an enriched dimension. We now have the data with multiple predictors and the dependent variable outcome (created by taking a lead operation on the flag, that is, indicator whether there was a power outage the next day).

We are challenged with the vanilla classification problem with a binary outcome, that is, 1 and O.

Note

As a part of the modeling exercise, we need to explore in depth the variables for the classification model, study correlation, ...

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