IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier.
Rong ZhuYong WangJin-Xing LiuLing-Yun DaiPublished in: BMC bioinformatics (2021)
We compared IPCARF with the existing LRLSLDA, LRLSLDA-LNCSIM, TPGLDA, NPCMF, and ncPred prediction methods, which have shown excellent performance in predicting lncRNA-disease associations. The compared results of 10-fold cross-validation procedures show that the predictions of the IPCARF method are better than those of the other compared methods.