Title
Research On Auto-Fluorescence Spectrogram For Colorectal Carcinoma With Data Mining
Keywords
Colorectal carcinoma auto-fluorescence spectrogram data; Index-tree; KNN by counting
Abstract
Data classification is an important data mining role in biomedicine. This paper proposes a method to analyze Colorectal Carcinoma Auto-Fluorescence Spectrogram data based on Counting KNN Algorithm after analyzing the characteristics of biomedicine data. Though Counting KNN Algorithm for classification is simple and effective, it doesn't deal with biomedicine data well. After analyzing the algorithm performance, a novel Counting KNN algorithm by index tree is presented. Experiments show that this method outperforms the distance-based voting kNN, and C-kNN. More importantly it is a method that works for ordinal, nominal or mixed data. © 2007 IEEE.
Publication Date
10-23-2007
Publication Title
2007 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE
Number of Pages
1307-1310
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICBBE.2007.337
Copyright Status
Unknown
Socpus ID
35348917570 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/35348917570
STARS Citation
Liao, Zhifang; Fan, Xiaoping; Liao, Zhining; and Qu, Zhihua, "Research On Auto-Fluorescence Spectrogram For Colorectal Carcinoma With Data Mining" (2007). Scopus Export 2000s. 6651.
https://stars.library.ucf.edu/scopus2000/6651