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Schizophrenia detection via lobe-wise and overall EEG features using VMD and bayesian-optimized machine learning models. [PDF]
Front NeurosciSravanthi GS, Sharma LD.
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Fundamenta Informaticae, 2021
The k Nearest Neighbor (KNN) algorithm has been widely applied in various supervised learning tasks due to its simplicity and effectiveness. However, the quality of KNN decision making is directly affected by the quality of the neighborhoods in the modeling space.
Le, Linh, Xie, Ying, Raghavan, Vijay V.
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The k Nearest Neighbor (KNN) algorithm has been widely applied in various supervised learning tasks due to its simplicity and effectiveness. However, the quality of KNN decision making is directly affected by the quality of the neighborhoods in the modeling space.
Le, Linh, Xie, Ying, Raghavan, Vijay V.
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International Journal of Information Security and Privacy, 2021
On one hand, there are many proposed intrusion detection systems (IDSs) in the literature. On the other hand, many studies try to deduce the important features that can best detect attacks. This paper presents a new and an easy-to-implement approach to intrusion detection, named distance sum-based k-nearest neighbors (DS-kNN), which is an improved ...
Redha Taguelmimt, Rachid Beghdad
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On one hand, there are many proposed intrusion detection systems (IDSs) in the literature. On the other hand, many studies try to deduce the important features that can best detect attacks. This paper presents a new and an easy-to-implement approach to intrusion detection, named distance sum-based k-nearest neighbors (DS-kNN), which is an improved ...
Redha Taguelmimt, Rachid Beghdad
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kNN-P: A kNN classifier optimized by P systems
Theoretical Computer Science, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Juan +3 more
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Proceedings of the 4th International Conference on Communication and Information Processing, 2018
K nearest neighbor (kNN) method is a popular classification method in data mining because of its simple implementation and significant classification performance. However, kNN do not scale well to big datasets. In this paper, CLUKER, a novel kNN regression method based on hierarchical clustering, is proposed.
Yi Xiang +3 more
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K nearest neighbor (kNN) method is a popular classification method in data mining because of its simple implementation and significant classification performance. However, kNN do not scale well to big datasets. In this paper, CLUKER, a novel kNN regression method based on hierarchical clustering, is proposed.
Yi Xiang +3 more
openaire +1 more source