Research on Auto-Fluorescence Spectrogram for Colorectal Carcinoma with Data Mining

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.