Exploration of Obesity Status of Indonesia Basic Health Research 2013 With Synthetic Minority Over-Sampling Techniques
نویسندگان
چکیده
منابع مشابه
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...
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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...
متن کاملClassification of Imbalanced Data Using Synthetic Over-Sampling Techniques
of the Thesis Classification of Imbalanced Data Using Synthetic Over-Sampling Techniques
متن کاملAn Analysis of Classification of Imbalanced Datasets by Using Synthetic Minority Over-Sampling Technique
Abstract—Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalance...
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ژورنال
عنوان ژورنال: Indonesian Journal of Statistics and Its Applications
سال: 2021
ISSN: 2599-0802
DOI: 10.29244/ijsa.v5i1p75-91