Data Mining and Machine Learning Applications

This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographi…

• YALIN KILIÇ TÜREL

This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographi…

• SERHAT ÖZEKES

In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science…

• CEM OKTAY GÜZELLER
• GÖKHAN AKSU
• MEHMET TAHA ESER

No abstract yet.

• NAZİF ÇALIŞ

Machine learning is a science which was found and developed as a subfield of artificial intelligence in the 1950s. The first steps of machine learning goes back to the 1950s but there were no significant researches and developments on this science. However, in the 1990s, the researches on this field restarted, develop…

• ÖZER ÇELİK

Aim: Heart disease detection using machine learning methods has been an outstanding research topic as heart diseases continue to be a burden on healthcare systems around the world. Therefore, in this study, the performances of machine learning methods for predictive classification of coronary heart disease were compar…

• FATMA HİLAL YAĞIN

Aim: Heart disease detection using machine learning methods has been an outstanding research topic as heart diseases continue to be a burden on healthcare systems around the world. Therefore, in this study, the performances of machine learning methods for predictive classification of coronary heart disease were compar…

• RÜSTEM YILMAZ

Abstract: This paper gives an integrated view of implementing automated diagnostic systems for clinical decision‐making. Because of the importance of making the right decision, better classification procedures are necessary for clinical decisions. The major objective of the paper is to be a guide for readers who want…

• ELİF DERYA ÜBEYLİ

No abstract yet.

• ERHAN AKIN

Artificial Neural Networks are commonly used to solve problems in many areas, such as classification, pattern recognition, and image processing. The most challenging and critical phase of an Artificial Neural Networks is related with its training process. The main challenge in the training process is finding optimal n…

• BAHAEDDİN TÜRKOĞLU

Artificial Neural Networks are commonly used to solve problems in many areas, such as classification, pattern recognition, and image processing. The most challenging and critical phase of an Artificial Neural Networks is related with its training process. The main challenge in the training process is finding optimal n…

• ERSİN KAYA

The most common blood disease worldwide is anemia, defined by the World Health Organization as a condition in which the red blood cell count or oxygen-carrying capacity is insufficient. As both a disease and a symptom, this condition affects the quality of life. Early and correct diagnosis of the type of anemia is vit…

• BİRGÜL ÖNEÇ
• NİLÜFER YURTAY