DDMarkerFAST: DDMarker FeAture SelecTion

In yu-shang/DDMarkerFAST: Diagnose and Detect Markers in Extracellular Circulating Feature Selection Method

Description

The Feature Selection Method of Diagnose and Detect Markers in Extracellular Circulating

results = DDMarkerFAST(data, ...);

Arguments

data	Data matrix, the first column must contain the feature types, eg. BLOOD, URINE, ... , and the following ones should be the features just like the references [1] and [2] did.
method	-method should be ( "svm", "adaboost", "bayes", "cart", "c5" ), "svm" denotes Support Vector Machines, the most stable method in biomarkers diagnosis, "adaboost" denotes AdaBoost, also known as the the most efficiency and accuracy method, "bayes" denotes Naive Bayes Cluster, "cart" denotes Recursive Partitioning and Regression Trees, "c5" denotes Decision Trees. default: "svm"

Details

models = DDMarkerFAST(data = data, method = "svm");

Value

The R function, DDMarkerFAST returns an object of list:

class	shows the method used.
names	shows the model attributes, which can be used in the prediction method, the more details will be found in references.
vardep.summary, xlevels, ylevels	adaboost and cart will return the elements, the more details will be found in references.

Author(s)

Yu Shang (JLU & UGA) [e-mail]
Qiong Yu (JLU & UGA) [e-mail] [e-mail]
Huansheng Cao (UGA) [e-mail]
Guoqing Liu (IMUST & UGA) [e-mail] [e-mail]
Xiufeng Liu (GZUCM & UGA) [e-mail] [e-mail]
Hao Wu (BIT & UGA) [e-mail] [e-mail]
Yan Wang (JLU & UGA) [e-mail]
Ying Xu (JLU & UGA) [e-mail] [e-mail]

Maintainer: Yu Shang (JLU & UGA) [e-mail]

References

citation("DDMarkerFAST");
[1] Juan Cui, et al. (2011) An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucleic Acids Research, 39: 1197-1207
[2] Juan Cui, et al. (2008) Computational prediction of human proteins that can be secreted into the bloodstream. BIOINFORMATICS, Vol.24 no. 20 2008 pages 2370-2375
[3] http://bioinfosrv1.bmb.uga.edu/DMarker/
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[26] Reyzin L, et al. (2006) How boosting the margin can also boost classifier complexity. In: Proceedings of the 23rd international conference on machine learning.

See Also

DDMarkerFAST-package DDMarkerP-method DDMarker NAR

Examples

models = DDMarkerFAST();

yu-shang/DDMarkerFAST documentation built on May 4, 2019, 5:34 p.m.