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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

Kemahiran: Python, Machine Learning (ML), Deep Learning, Algoritma

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Tentang Majikan:
( 0 ulasan ) Sudbury, Canada

ID Projek: #24590613

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9 pekerja bebas membida secara purata $177 untuk pekerjaan ini


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$250 CAD dalam 5 hari
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$250 CAD dalam 3 hari
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