Name
Title | ||
|---|---|---|
A sequential feature extraction approach for naïve bayes classification of microarray data |
Abstract | ||
|---|---|---|
Accurate classification of microarray data plays a vital role in cancer prediction and diagnosis. Previous studies have demonstrated the usefulness of naive Bayes classifier in solving various classification problems. In microarray data analysis, however, the conditional independence assumption embedded in the classifier itself and the characteristics of microarray data, e.g. the extremely high dimensionality, may severely affect the classification performance of naive Bayes classifier. This paper presents a sequential feature extraction approach for naive Bayes classification of microarray data. The proposed approach consists of feature selection by stepwise regression and feature transformation by class-conditional independent component analysis. Experimental results on five microarray datasets demonstrate the effectiveness of the proposed approach in improving the performance of naive Bayes classifier in microarray data analysis. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.eswa.2009.01.075 | Expert Syst. Appl. |
Keywords | Field | DocType |
bayes classification,independent component analysis (ica),sequential feature extraction approach,feature extraction,microarray data analysis,naive bayes classification,naïve bayes,microarray data,microarray datasets,various classification problem,naive bayes classifier,stepwise regression,accurate classification,classification performance,class-conditional independent component analysis,feature selection,naive bayes,conditional independence,independent component analysis,bayes classifier | Data mining,Feature selection,Computer science,Artificial intelligence,Classifier (linguistics),Bayes error rate,Pattern recognition,Naive Bayes classifier,Conditional independence,Feature extraction,Independent component analysis,Bayes classifier,Machine learning | Journal |
Volume | Issue | ISSN |
36 | 6 | Expert Systems With Applications |
Citations | PageRank | References |
21 | 0.80 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li-Wei Fan | 1 | 71 | 5.36 |
| Kim-leng Poh | 2 | 279 | 30.30 |
| P. Zhou | 3 | 372 | 26.80 |