Table 9

Worst case time performance (in ms) of classification algorithms
Data set Diabetes Alzheimer’s Antibodies Avg. (in ms) Rank
Random Tree 1809 491 1478 1260 1
KNN 3016 607 910 1511 2
Hyper Pipes 2486 602 2180 1756 3
Naïve Bayes 4780 1158 2480 2806 4
VFI 7440 1357 3000 3932 5
J48 16581 1385 11731 9899 6
K star 25974 2348 6341 11555 7
SVM 10496 2722 29008 14076 8
R. Forest 50087 8032 21452 26524 9
M5P 50290 8563 23452 27435 10
Bayes Net 55672 9031 25000 29901 11
K-means 85955 12405 29658 42672 12
SLR 632840 48215 605365 428806 13
LDA 658668 869523 632983 720391 14
Logistic R. 1589092 1146783 1315256 1350377 15
ASC 5444533 2465021 4565896 4158483 16
MLP dnf dnf dnf NA 17

Table showing time performance in milliseconds over >1000 peptides for three datasets. Random Tree, KNN, Hyper Pipes and VFI were among the fastest. MLP were among the slowest with dnf: “Did not finish”. Time measurements less than 10 seconds are marked in bold.

Kukreja et al.

Kukreja et al. BMC Bioinformatics 2012 13:139   doi:10.1186/1471-2105-13-139

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