Title
A New Data Processing Approach Research To Auto-Fluorescence Spectrogram For Colorectal Carcinoma
Keywords
ckNN; Colorectal carcinoma auto-fluorescence spectrogram data; Index-tree structure
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. The new method improves the efficiency by using a tree structure index with the same accuracy. Experiments show that this method outperforms the distance-based voting kNN for accuracy, and ckNN for efficiency.
Publication Date
12-1-2007
Publication Title
Proceedings of the 26th Chinese Control Conference, CCC 2007
Number of Pages
628-632
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CHICC.2006.4347584
Copyright Status
Unknown
Socpus ID
37749024309 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/37749024309
STARS Citation
Fan, Xiaoping; Liao, Zhifang; Chen, Yuzhou; Liao, Zhining; and Qu, Zhihua, "A New Data Processing Approach Research To Auto-Fluorescence Spectrogram For Colorectal Carcinoma" (2007). Scopus Export 2000s. 6240.
https://stars.library.ucf.edu/scopus2000/6240