Applied general linear regression model in data mining /
تطبيق الانحدار الخطي العام في مجال التنقيب عن البيانات
Khaled Mohamed Mohamed Ftouh Elbolkiny ; Supervised Ahmed Amin Elsheikh , Yasmin Ibrahim Mohamed
- Cairo : Khaled Mohamed Mohamed Ftouh Elbolkiny , 2018
- 68 Leaves ; 30cm
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Statistics and Econometrics
The field of data mining (DM) and knowledge discovery in databases is a recent development. During the operation of organizations, information is accumulated gradually and the size of data grows rapidly. Although the computer storage technology has developed fast enough to store such enormous data, traditional statistical methods are not capable of managing such huge scale databases. Facing with todays complex and information-rich databases, to extract important and useful knowledge hidden in these data has become a crucial step in now a days competitive world. Data mining is the exploration and analysis of large quantities of data in order to discover meaningful patterns and rules (Berry and Gordon, 2004).Data mining concept can be defined as the technique of identifying patterns and relationships within large databases through the use of advanced statistical methods.The ultimate goal of DM is to transit from exploring data, through exploiting the results, to explain the data and their results. In order to do data mining to achieve that transition successfully, it must pass through the heart of statistics. On the other hand, statistical analysis must be rigorously scaled up to the level of data volume ( El-Afify, 2014)