| dc.contributor.author | ประยุทธ์ ศิลป์ชัยนาม | en_US |
| dc.date.accessioned | 2019-09-11T03:41:33Z | |
| dc.date.available | 2019-09-11T03:41:33Z | |
| dc.date.issued | 2019 | |
| dc.identifier.uri | http://repository.rmutr.ac.th/123456789/1082 | |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1082 | |
| dc.description.abstract | This research aims to develop and compare models for identifying chronic kidney disease patients.
By using serveral Data mining techniques including K-nearest neighbor, decision tree, Random Forest, support
vector machine and Naïve Bayes are used to test the classification of patients by using chronic kidney disease
data from Apollo Hospital India By storing it in a relational database. Which has good efficiency, can support
fast data transmission which responds to current information usage. And analyze to summarize with the
image analysis system to be able to understand the information easily. | en_US |
| dc.language.iso | TH | en_US |
| dc.publisher | มหาวิทยาลัยศรีปทุม | en_US |
| dc.subject | Visualization | en_US |
| dc.subject | Data Mining-nearest neighbor | en_US |
| dc.subject | decision tree | en_US |
| dc.subject | artificial neural network | en_US |
| dc.subject | support vector machine | en_US |
| dc.subject | Naïve Bayes | en_US |
| dc.title | Data Classification Model for Chronic Kidney Disease using data mining Technique and Visualization | en_US |
| dc.title.alternative | การสร้างแบบจําลองจําแนกกลุ่มผู้ป่วยโรคไตเรื้อรังโดยใช้เทคนิคเหมืองข้อมูลและวิชวลไลเซชั่น | en_US |
| dc.type | Article | en_US |
