How To Predict Water Pumps Failure in Tanzania using CatBoost Libraryby@sagol

How To Predict Water Pumps Failure in Tanzania using CatBoost Library

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The goal of the competition is to build a model that predicts the functionality of water supply points. The data has 59400 rows and 40 columns without the label that comes in a separate file. The metric used for this competition is the classification rate, which calculates the. percentage of rows where the predicted class in the. submission matches the actual class. in the model. The older the waterpoint, the higher the probability that it is not functioning, mostly before the 80s. The number of broken water points there is the majority of the broken water. We can assume that some of the payments can positively affect keeping the. state in a working state.

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