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This is an highly imbalanced data with only 1.72% minority and 98.28% majority class, i will be explaining Up and down sampling and effect of sampling before and while doing cross validation. Model has been evaluated using precision recall curve.
Repository where it is intended to address the challenge of LATAM Airlines, which consists of predicting the probability of delay of flights that land or take off from the Santiago de Chile airport (SCL)
The company has collected historical customer and claims data and wants to use it to develop a machine learning model that can predict whether a customer will file an insurance claim in the next year.
Light-weight package for classification metrics computed on streams or minibatches of data. Mainly for area under the curve (AUC) of precision-recall (PR) or receiver operating characteristic (ROC) curves. Supports multi-class setting with either macro- or micro aggregation..
Run histogram-based gradient boosted trees binary classifier on generated data and interpret results with standard metrics, SHAP, and supervised clustering