Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities
The KNN algorithm is one of the most famous algorithms in machine learning and data mining. It does not preprocess the data before classification, which leads to longer time and more errors. To solve the problems, this paper first proposes a PK-means++ algorithm, which can better ensure the stabilit...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5524388 |
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| _version_ | 1832568472002887680 |
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| author | Haiyan Wang Peidi Xu Jinghua Zhao |
| author_facet | Haiyan Wang Peidi Xu Jinghua Zhao |
| author_sort | Haiyan Wang |
| collection | DOAJ |
| description | The KNN algorithm is one of the most famous algorithms in machine learning and data mining. It does not preprocess the data before classification, which leads to longer time and more errors. To solve the problems, this paper first proposes a PK-means++ algorithm, which can better ensure the stability of a random experiment. Then, based on it and spherical region division, an improved KNNPK+ is proposed. The algorithm can select the center of the spherical region appropriately and then construct an initial classifier for the training set to improve the accuracy and time of classification. |
| format | Article |
| id | doaj-art-fd90e205444842c8a220a62d0cc1d30b |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-fd90e205444842c8a220a62d0cc1d30b2025-02-03T00:58:59ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55243885524388Improved KNN Algorithm Based on Preprocessing of Center in Smart CitiesHaiyan Wang0Peidi Xu1Jinghua Zhao2College of Computer Science and Technology, Changchun University, Changchun 130022, ChinaCollege of Computer, Jilin Normal University, Siping 136000, ChinaCollege of Computer, Jilin Normal University, Siping 136000, ChinaThe KNN algorithm is one of the most famous algorithms in machine learning and data mining. It does not preprocess the data before classification, which leads to longer time and more errors. To solve the problems, this paper first proposes a PK-means++ algorithm, which can better ensure the stability of a random experiment. Then, based on it and spherical region division, an improved KNNPK+ is proposed. The algorithm can select the center of the spherical region appropriately and then construct an initial classifier for the training set to improve the accuracy and time of classification.http://dx.doi.org/10.1155/2021/5524388 |
| spellingShingle | Haiyan Wang Peidi Xu Jinghua Zhao Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities Complexity |
| title | Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities |
| title_full | Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities |
| title_fullStr | Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities |
| title_full_unstemmed | Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities |
| title_short | Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities |
| title_sort | improved knn algorithm based on preprocessing of center in smart cities |
| url | http://dx.doi.org/10.1155/2021/5524388 |
| work_keys_str_mv | AT haiyanwang improvedknnalgorithmbasedonpreprocessingofcenterinsmartcities AT peidixu improvedknnalgorithmbasedonpreprocessingofcenterinsmartcities AT jinghuazhao improvedknnalgorithmbasedonpreprocessingofcenterinsmartcities |