Table 3 Models performance for algometric pain (AP), fibromyalgia impact questionnaire (FIQ), pain catastrophizing scale (PCS), and Pittsburgh sleep quality index (PSQI).

Models for AP

Fast KAN-BCO

0.0018

0.0422

0.9836

0.0054

0.0732

0.9517

Fast KAN

0.0036

0.0597

0.9671

0.0064

0.0800

0.9424

Linear regression

0.0173

0.1314

0.8406

0.0150

0.1226

0.8645

MLP-LGBFS

0.0047

0.0689

0.9562

0.0138

0.1176

0.8755

MLP-ADAM

0.0111

0.1055

0.8972

0.0086

0.0929

0.9223

Models for FIQ

Fast KAN-BCO

0.0086

0.0927

0.8451

0.0315

0.1776

0.5081

Fast KAN

0.0105

0.1023

0.8115

0.0120

0.1095

0.8132

Linear regression

0.0172

0.1311

0.6903

0.0183

0.1353

0.7145

MLP-LGBFS

0.0047

0.0689

0.9562

0.0138

0.1176

0.8755

MLP-ADAM

0.0181

0.1346

0.6736

0.0202

0.1422

0.6848

Models for PCS

Fast KAN-BCO

0.0013

0.0358

0.9615

0.0058

0.0765

0.8011

Fast KAN

0.0078

0.0881

0.7672

0.0090

0.0951

0.6926

Linear regression

0.0045

0.0667

0.8663

0.0025

0.0498

0.9156

MLP-LGBFS

0.0009

0.0301

0.9728

0.0018

0.0427

0.9378

MLP-ADAM

0.0049

0.0703

0.8516

0.0032

0.0566

0.8909

Models for PSQI

Fast KAN-BCO

0.0006

0.0237

0.9917

0.0114

0.1067

0.8137

Fast KAN

0.0025

0.0504

0.9626

0.0099

0.0994

0.8385

Linear regression

0.0065

0.0805

0.9046

0.0058

0.0764

0.9044

MLP-LGBFS

0.0006

0.0254

0.9905

0.0021

0.0461

0.9652

MLP-ADAM

0.0082

0.0903

0.8798

0.0074

0.0861

0.8788