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Creating CMTNN for majority class in a data set and SMOTE for minority class

The Project contains an highly imbalanced data as it is divided into two class Majority class and minority class so on the majority class we apply CMTNN (Complementary neural Network ) and on Minority class we apply SMOTE which is oversampling method and then we apply five different types of classifiers and check its AUC and G mean

Compétences : Python, Machine Learning (ML), Deep Learning, Algorithme

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Concernant l'employeur :
( 0 commentaires ) Sudbury, Canada

Nº du projet : #24590613

Décerné à:


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9 freelance font une offre moyenne de $177 pour ce travail


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