|
Prerequisites
|
None
|
|
Language of Instruction
|
Turkish
|
|
Responsible
|
Assoc. Prof. Gülay KARAHAN
|
|
Instructors
|
1-)Doçent Dr. Gülay Karahan
|
|
Assistants
|
-
|
|
Resources
|
R1. Argüden, Y., Erşahin, B. (2008). Veri Madenciliği. ARGE Danışmanlık Yayınları.ISBN:978-975-93641-9-9.
R2. Mailund, T. (2017). Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist. Library of Congress Control Number: 2017934529. ISBN-13 (pbk): 978-1-4842-2670-4.
R3. Şeker, S.E. (2014). Weka ile veri madenciliği. Bilgisayar kavramları yayınları
|
|
Supplementary Book
|
-
|
|
Goals
|
Provide competence to students in knowledge of data mining, data and information, information discovery in databases, traditional statistical methods, artificial neural networks, decision trees, Bayes theorem, applications and advanced techniques
|
|
Content
|
Data mining functions include decision trees, bayes, regression, clustering, using R packets, creating graphics, data mining applications with R and WEKA.
|