Application of the random forest classification algorithm to a SELDI-TOF proteomics study in the setting of a cancer prevention trial

被引：90

作者：

Izmirlian, G ^{[1
]}

机构：

[1] NCI, DHHS, Div Canc Prevent, Biometry Res Grp, Rockville, MD 20852 USA

来源：

APPLICATIONS OF BIOINFORMATICS IN CANCER DETECTION | 2004年 / 1020卷

关键词：

random forest (RF) algorithm; SELDI-TOF; cancer; classifier; classification tree (CT); detection; prevention; MDM; statistic;

D O I：

10.1196/annals.1310.015

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

A thorough discussion of the random forest (RF) algorithm as it relates to a SELDI-TOF proteomics study is presented, with special emphasis on its application for cancer prevention: specifically, what makes it an efficient, yet reliable classifier, and what makes it optimal among the many available approaches. The main body of the paper treats the particulars of how to successfully apply the RF algorithm in a proteomics profiling study to construct a classifier and discover peak intensities most likely responsible for the separation between the classes.

引用

页码：154 / 174

页数：21

共 22 条

[1] CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].

BENJAMINI, Y ;

HOCHBERG, Y .

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300

[2] Random forests [J].

Breiman, L .

MACHINE LEARNING, 2001, 45 (01) :5-32

[3]

Breiman L, 1998, ANN STAT, V26, P801

[4] Bagging predictors [J].

Breiman, L .

MACHINE LEARNING, 1996, 24 (02) :123-140

[5]

BREIMAN L, 2003, RANDOM FOREST PACKAG

[6]

Breiman L., 2017, Classification And Regression Trees, DOI [10.1201/9781315139470, DOI 10.1201/9781315139470]

[7] Proteomic patterns in serum and identification of ovarian cancer [J].

Diamandis, EP .

LANCET, 2002, 360 (9327) :170-170

[8]

Durrett R., 1991, PROBABILITY THEORY E

[9] 1977 RIETZ LECTURE - BOOTSTRAP METHODS - ANOTHER LOOK AT THE JACKKNIFE [J].

EFRON, B .

ANNALS OF STATISTICS, 1979, 7 (01) :1-26

[10]

Efron B., 1995, CROSS VALIDATION BOO

← 1 2 3 →