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Classification using all measures

GC Geetha Soujanya Chilla
LY Ling Yun Yeow
QC Qian Hui Chew
KS Kang Sim
KP K. N. Bhanu Prakash
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In the second set of 3 analyses, analyses 6–8 of Table ​Table1,1, all subcortical and cortical measures were used, either by merging feature sets or through Ensemble methods. For direct comparison with Ensemble methods, we carried out analysis 6 of Table ​Table1,1, where all subcortical and cortical measures were merged, redundant variables were removed and feature selection and classification were carried out in a manner similar to independent measures classification. In analysis 7, we employed three different input classifiers for Ensemble classification, where input classifiers were trained on subcortical volumes, cortical volumes and remaining cortical measures respectively as shown in Table ​Table1.1. In analysis 8, five different input classifiers trained on independent measure sets, from analyses 1–5, are used for Ensemble classification.

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