DDMarkerFAST: DDMarker FeAture SelecTion

Description Arguments Details Value Author(s) References See Also Examples


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

results = DDMarkerFAST(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 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"


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


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.


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

Maintainer: Yu Shang (JLU & UGA) [email protected]


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[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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See Also

DDMarkerFAST-package DDMarkerP-method DDMarker NAR


models = DDMarkerFAST();

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