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| Title Details: | |
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Data Types, Quality and Preprocessing |
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| Authors: |
Verykios, Vasileios Kagklis, Vasileios Stavropoulos, Ilias |
| Reviewer: |
Kalles, Dimitrios |
| Description: | |
| Abstract: |
In this chapter the student understands that data, its types and quality are an integral part of the data mining process. It becomes abundantly clear that the quality of the data largely determines the quality of the results of data mining. Those parameters of the data that affect their quality must be clear so that one is able to evaluate and improve them. Data preprocessing is the most laborious and time-consuming part in the process of discovering knowledge from data. The aim of this chapter is also to familiarize the student with all the different forms of data preprocessing and to be able to apply them as well as to be able to apply these techniques through a tool such as R.
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| Linguistic Editors: |
Spanaka, Adamantia |
| Graphic Editors: |
Filoni, Valentina |
| Type: |
Chapter |
| Creation Date: | 2015 |
| Item Details: | |
| License: |
http://creativecommons.org/licenses/by-nc-nd/3.0/gr |
| Handle | http://hdl.handle.net/11419/2968 |
| Bibliographic Reference: | Verykios, V., Kagklis, V., & Stavropoulos, I. (2015). Data Types, Quality and Preprocessing [Chapter]. In Verykios, V., Kagklis, V., & Stavropoulos, E. 2015. Data science through the R language [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/2968 |
| Language: |
Greek |
| Is Part of: |
Data science through the R language |
| Publication Origin: |
Kallipos, Open Academic Editions |