Double weighted k nearest neighbours for binary classification of high dimensional genomic data
Abstract High dimensional gene expression datasets consist of a large number of genes, many of which do not play a significant role in classifying tissue samples. The high dimensional nature of this type of data, characterized by a large number of gene features substantially exceeding its sample siz...
Saved in:
| Main Authors: | Amjad Ali, Zardad Khan, Hailiang Du, Saeed Aldahmani |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-97505-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification
by: Maulidia Rahmah Hidayah, et al.
Published: (2017-05-01) -
Margin weighted robust discriminant score for feature selection in imbalanced gene expression classification
by: Sheema Gul, et al.
Published: (2025-01-01) -
Margin weighted robust discriminant score for feature selection in imbalanced gene expression classification.
by: Sheema Gul, et al.
Published: (2025-01-01) -
Comparison between Logistic Regression and K-Nearest Neighbour Techniques with Application on Thalassemia Patients in Mosul
by: Mohammed Al jbory, et al.
Published: (2025-06-01) -
Enhancing Clustering Efficiency in Heterogeneous Wireless Sensor Network Protocols Using the K-Nearest Neighbours Algorithm
by: Abdulla Juwaied, et al.
Published: (2025-02-01)