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Table 8 The influence of the number of classifiers on classification results

From: Localized instance fusion of MRI data of Alzheimer’s disease for classification based on instance transfer ensemble learning

Number of sub-classifiers (Deviations)

Kernel

SD_GraTrans_Opt_SamSel+TD_train

(Mean, std)

SD_GraTrans_FG + TD_train

(Mean, std)

TD_train

(Mean, std)

25

Linear

(81.67%, 0)

(71.67%, 0)

(71.67%, 0)

RBF

(78.33%, 0)

(78.33%, 0)

(76.67%, 0)

10

Linear

(81.67%, 0.0079)

(79.67%, 0.0189)

(71.67%, 0)

RBF

(74.33%, 0.0161)

(77.5%, 0.0425)

(76.67%, 0)

5

Linear

(81.33%, 0.0070)

(80%, 0.0192)

(71.67%, 0)

RBF

(74.67%, 0.0205)

(76.33%, 0.0362)

(76.67%, 0)

  1. The italicized data represents the highest classification accuracy under the same experimental conditions