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  7. მონაცემთა მოძიების მეთოდები SQL- ის რესურსების გამოყენებით
 
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მონაცემთა მოძიების მეთოდები SQL- ის რესურსების გამოყენებით

Date Issued
2019
Author(s)
შავკაციშვილი, ჯულია  
Advisor
არჩუაძე, მაია  
Institution
Ivane Javakhishvili Tbilisi State University  
Faculty
Faculty of Exact and Natural Sciences  
Publisher
Ivane Javakhishvili Tbilisi State University  
URI
https://openscience.ge/handle/1/1603
Abstract
SQL Server has been a leader in predictive analytics since the 2000 release, by providing data mining in Analysis Services. SQL Server Data Mining provides an integrated platform for predictive analytics that encompasses data cleansing and preparation, machine learning, and reporting. SQL Server Data Mining includes multiple standard algorithms, including EM and K-means clustering models, neural networks, logistic regression and linear regression, decision trees, and naive bayes classifiers. All models have integrated visualizations to help you develop, refine, and evaluate your models.
Today there are many algorithms and methods used for analysis of data. The main problem is to find a suitable algorithm for data retrieval in case of a particular problem. The work is examined and analyzed by the factors influencing the selection of the algorithm.
Master's thesis may be useful for scientific workers, teachers, doctoral students, graduate students, bachelors and students of higher education institutions. Its main conclusions can be used to conduct further studies in various organizations, as well as in pedagogic practice.
Subjects

SQL Server Data minin...

Degree Name
Master of Information Technology
Degree Discipline
ინფორმაციული ტექნოლოგიები. Information Technology
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MA Thesis Shavkacishvili Julia.pdf

Description
მონაცემთა მოძიების მეთოდები SQL- ის რესურსების გამოყენებით
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972.37 KB

Format

Adobe PDF

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(MD5):a6d08c1ab543a8a3a47826fb58e35205

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