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247.252  Articles
1 of 24.726 pages  |  10  records  |  more records»
Detecting fraud in the healthcare insurance dataset is challenging due to severe class imbalance, where fraud cases are rare compared to non-fraud cases. Various techniques have been applied to address this problem, such as oversampling and undersampling ... see more

Handling imbalanced dataset has their own challenge. Inappropriate step during the pre-processing phase with imbalanced data could bring the negative effect on prediction result. The accuracy score seems high, but actually there are many problems on recal... see more

Imbalanced dataset merupakan hal yang sering ditemukan secara alami dalam proses penambangan data. Kondisi ini sangat mempengaruhi keakuratan klasifikasi data seperti yang terjadi dalam klasifikasi komentar program Kampus Merdeka yang peneliti lakukan. Pe... see more

One of the problems that are often faced by classifier algorithms is related to the problem of imbalanced data. One of the recommended improvement methods at the data level is to balance the number of data in different classes by enlarging the sample to t... see more

The extremely skewed data in artificial intelligence, machine learning, and data mining cases are often given misleading results. It is caused because machine learning algorithms are designated to work best with balanced data. However, we often meet with ... see more

The extremely skewed data in artificial intelligence, machine learning, and data mining cases are often given misleading results. It is caused because machine learning algorithms are designated to work best with balanced data. However, we often meet with ... see more

Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algo... see more

The class imbalance is a condition when one class has a higher percentage than the other then it can affect the accuracy. One method in data mining that can be used to classification is logistic regression method. The method used in this research is RWO-s... see more

Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algo... see more

1 of 24.726 pages  |  10  records  |  more records»