A Back Propagation Neural Network Model with the Synthetic Minority Over-Sampling Technique for Construction Company Bankruptcy Prediction

ovarian cancer classification using hybrid synthetic minority over-sampling technique and neural network

every woman is at risk of ovarian cancer; about 90 percent of women who develop ovarian cancer are above 40 years of age, with the high number of ovarian cancers occurring at the age of 60 years and above. early and correct diagnosis of ovarian cancer can allow proper treatment and as a result reduce the mortality rate. in this paper, we proposed a hybrid of synthetic minority over-sampling tec...

SMOTE: Synthetic Minority Over-sampling Technique

An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of “normal” examples with only a small percentage of “abnormal” or “interesting” examples. It is also the case that the cost of misclassifying an abnormal (i...

An Improved Intrusion Detection Approach using Synthetic Minority Over-Sampling Technique and Deep Belief Network

Improving accuracy of students' final grade prediction model using optimal equal width binning and synthetic minority over-sampling technique

There is a perpetual elevation in demand for higher education in the last decade all over the world; therefore, the need for improving the education system is imminent. Educational data mining is a newly-visible area in the field of data mining and it can be applied to better understanding the educational systems in Bangladesh. In this research, we present how data can be preprocessed using a d...

An Adaptive Fuzzy Neural Network Model for Bankruptcy Prediction of Listed Companies on the Tehran Stock Exchange

Nowadays, prediction of corporate bankruptcy is one of the most important issues which have received great attentions among academia and practitioners. Although several studies have been accomplished in the field of bankruptcy prediction, less attention has been devoted for proposing a systematic approach based on fuzzy neural networks.  The present study proposes fuzzy neural networks to predi...