论文信息 - Comparison of supervised models in hepatocellular carcinoma tumor classification based on expression data using principal component analysis (PCA) - 字舞流文

Comparison of supervised models in hepatocellular carcinoma tumor classification based on expression data using principal component analysis (PCA)

Devvi Sarwinda | Titin Siswantining | Alhadi Bustamam | Anggrainy Togi Marito Siregar | A. Bustamam | T. Siswantining | Devvi Sarwinda

[1] P. Galle,et al. Microarray-Based Gene Expression Analysis of Hepatocellular Carcinoma , 2010, Current genomics.

[2] Alhadi Bustamam,et al. Clustering and analyzing microarray data of lymphoma using singular value decomposition (SVD) and hybrid clustering , 2018 .

[3] William F. Christensen,et al. Methods of Multivariate Analysis: Rencher/Methods , 2012 .

[4] A. Wosiak. Principal Component Analysis based on data characteristics for dimensionality reduction of ECG recordings in arrhythmia classification , 2019, Open Physics.

[5] Makoto Aoshima,et al. Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations , 2012, J. Multivar. Anal..

[6] Derek S. Young,et al. Some dimension reduction strategies for the analysis of survey data , 2017, Journal of Big Data.

[7] T. Siswantining,et al. Ovarian Cancer Classification using Bayesian Logistic Regression , 2019, IOP Conference Series: Materials Science and Engineering.