considered variations offers a clear advantage over the benchmark algorithms. However, in terms of AUC and top-decile lift …

The area under Receiver Operating Characteristic (ROC) curve, also known as the AUC-index, is commonly used for ranking … the performance of data mining models. The AUC has many merits, such as objectivity and ease of interpretation. However … proposed AUK-index compensates for the above basic flaw of the AUC by being sensitive to the class distribution. Therefore it …

characteristics curve (AUC) maximization based on the new emerged support vector machines (SVM) techniques. Three main SVM models with …

suggested model for link prediction is proposed in this paper. The suggested HMELA model makes use of AUC scores to predict new … selected data sets, the area under the curve (AUC) scores were greater than when individual techniques were applied to the same … data sets. Using the HMELA technique, the maximum AUC score in the Facebook data set has been increased by 10.3 per cent …

, specificity, and the complexity, are analyzed by using firm level data in Turkey. This study has three main conclusions. As for …

transactionattributes, that is, asset specificity, transaction frequency, and uncertainty. The research is based on the theoretical …

, specificity, and the complexity, are analyzed by using firm level data in Turkey. This study has three main conclusions. As for …

, specificity, and the complexity, are analyzed by using firm level data in Turkey. This study has three main conclusions. As for …