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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:

Innovation22

Hi, I have read through your requirements and I am sure I can help you with this. I am a final year engineering student at IIT Kharagpur. I have substantial experience with Deep Learning and Computer [login to view URL] can l Plus

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Sam0072

hello sir , I am a machine learning engineer having 5+ years of experience . I have done many projects on image classification either in agriculture sector or in medical sectors. I have used many framework for object Plus

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

liveexperts123

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umg536

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crduran

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putinhuylo000532

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softbox06

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EngDinaa

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liqiangcn

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