1. A collective learning approach for semi-supervised data classification
- Author
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Nur Uylaş Satı
- Subjects
semi- supervised data classification ,clustering method ,supervised data classification ,machine learning ,mathematical programming ,yarı-gözetimli veri sınıflandırma ,kümeleme yöntemi ,gözetimli veri sınıflandırma ,makine öğrenme ,matematiksel programlama ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
Semi-supervised data classification is one of significant field of study in machine learning and data mining since it deals with datasets which consists both a few labeled and many unlabeled data. The researchers have interest in this field because in real life most of the datasets have this feature. In this paper we suggest a collective method for solving semi-supervised data classification problems. Examples in R1 presented and solved to gain a clear understanding. For comparison between state of art methods, well-known machine learning tool WEKA is used. Experiments are made on real-world datasets provided in UCI dataset repository. Results are shown in tables in terms of testing accuracies by use of ten fold cross validation.
- Published
- 2018