The Startup
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The Startup

How to Use CatBoost in a Multiclass Imbalance Dataset

CatBoost is a machine learning algorithm that uses gradient boosting on decision trees and is available as an open source library. Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do and generalizes them by allowing optimization of an arbitrary differentiable loss function.

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Tracyrenee

Tracyrenee

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I have close to five decades experience in the world of work, being in fast food, the military, business, non-profits, and the healthcare sector.