Data Preprocessing in Data Mining
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Fur...
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2015
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| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57671 |
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oai:scholar.dlu.edu.vn:DLU123456789-576712023-11-11T05:48:18Z Data Preprocessing in Data Mining Luengo, Julián Luengo, Julián Herrera, Francisco Data mining Electronic data processing Data preparation Engineering Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. 2015-08-20T03:29:43Z 2015-08-20T03:29:43Z 2015 Book 978-3-319-10247-4 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57671 en application/pdf Springer |
| institution |
Thư viện Trường Đại học Đà Lạt |
| collection |
Thư viện số |
| language |
English |
| topic |
Data mining Electronic data processing Data preparation Engineering |
| spellingShingle |
Data mining Electronic data processing Data preparation Engineering Luengo, Julián Luengo, Julián Herrera, Francisco Data Preprocessing in Data Mining |
| description |
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. |
| format |
Book |
| author |
Luengo, Julián Luengo, Julián Herrera, Francisco |
| author_facet |
Luengo, Julián Luengo, Julián Herrera, Francisco |
| author_sort |
Luengo, Julián |
| title |
Data Preprocessing in Data Mining |
| title_short |
Data Preprocessing in Data Mining |
| title_full |
Data Preprocessing in Data Mining |
| title_fullStr |
Data Preprocessing in Data Mining |
| title_full_unstemmed |
Data Preprocessing in Data Mining |
| title_sort |
data preprocessing in data mining |
| publisher |
Springer |
| publishDate |
2015 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57671 |
| _version_ |
1819776175629664256 |