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Table 4 PFC scores for the categorical features in the training set. The best performances are highlighted in bold

From: Exploiting mutual information for the imputation of static and dynamic mixed-type clinical data with an adaptive k-nearest neighbours approach

Features

Imputation methods

 

Amelia II

MICE

missForest

k-RN

wk-NN

k-RN

wk-NN MI

    

k=10

k=10

k=20

k=20

sex

0.4859

0.4416

0.4463

0.5160

0.3974

0.4831

0.3823

familiality

0.1646

0.1268

0.1372

0.0842

0.0823

0.0842

0.0738

genetics

0.3310

0.1781

0.1751

0.0956

0.0895

0.0956

0.0815

FTD

0.3295

0.2642

0.3565

0.2060

0.2003

0.1960

0.1903

onset site

0.2957

0.1516

0.1403

0.3672

0.1017

0.3484

0.0800

NIV

0.1111

0.0556

0.0537

0.0518

0.0480

0.0518

0.0235

PEG

0.0948

0.0150

0.0208

0.0069

0.0069

0.0069

0.0069

Average

0.2589

0.1761

0.1900

0.1897

0.1323

0.1809

0.1198

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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