Imbalanced dataset merupakan hal yang sering ditemukan secara alami dalam proses penambangan data. Kondisi ini sangat mempengaruhi keakuratan klasifikasi data seperti terjadi komentar program Kampus Merdeka peneliti lakukan. Penelitian akan fokus pada penanganan untuk meningkatkan kinerja berasal dari aplikasi Twitter. Data diklasifikasikan ke empat kelas yaitu 0 (untuk informasi), 1 opini), 2 ...

In a recent paper of ours [Hess & Field (1993). Vision Research, 33, 2663-2670], we claim that there was a predictable relationship between position errors and contrast errors for an undersampled system. In this paper we re-state our main points. We feel that the response to that paper by Levi and Klein in the accompanying article does not require us to produce changes in our original position....

Currently, fraud detection is employed in numerous domains, including banking, finance, insurance, government organizations, law enforcement, and so on. The amount of attempts has recently grown significantly, making critical when it comes to protecting your personal information or sensitive data. There are several forms issues, such as stolen credit cards, forged checks, deceptive accounting p...

Intrusion Detection Systems (IDS) figure as one of the leading solutions adopted in network security area to prevent intrusions and ensure data services security. However, this issue requires IDS be assertive efficient processing time. Undersampling techniques allow classifiers evaluated from smaller subsets a representative manner, aiming high metrics less There are several literature for proj...

Compressed sensing (CS) or compressive sampling provides a new sampling theory to reduce data acquisition, which says that compressible signals can be exactly reconstructed from highly incomplete sets of measurements. Very recently, the CS has been applied for seismic exploration and started to compact the traditional data acquisition. In this paper, we present an optimized sampling strategy fo...

Position judgements, which are exquisitely precise in the fovea, are markedly degraded in the periphery. In a recent article [Hess & Field (1993) Vision Research, 33, 2663-2670] argue that the poor representation of positional information in peripheral vision is a consequence of uncalibrated spatial disorder of cortical connections rather than due to undersampling of the retinal image. Specific...

In many data mining applications the imbalanced learning problem is becoming ubiquitous nowadays. When the data sets have an unequal distribution of samples among classes, then these data sets are known as imbalanced data sets. When such highly imbalanced data sets are given to any classifier, then classifier may misclassify the rare samples from the minority class. To deal with such type of im...