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Table 8 Baseline predictive model results

From: Machine learning approaches for predicting high cost high need patient expenditures in health care

Predicting objective

Model

Train

Test

R-squared

RMSE

RMSE for Top 10%

R-squared

RMSE

RMSE for Top 10%

PMPM

LR

0.145

0.306

0.264

0.141

0.306

0.264

LASSO

0.145

0.306

0.265

0.141

0.306

0.264

GBM

0.199

0.317

0.270

0.172

0.314

0.272

RNN

0.302

0.201

0.180

0.298

0.204

0.183

logPMPM

LR

0.401

0.306

0.265

0.402

0.306

0.264

LASSO

0.401

0.306

0.265

0.402

0.306

0.264

GBM

0.399

0.316

0.267

0.394

0.314

0.269

RNN

0.445

0.220

0.184

0.442

0.223

0.187

pctlPMPM

LR

0.399

0.306

0.265

0.400

0.306

0.264

LASSO

0.398

0.306

0.265

0.400

0.306

0.264

GBM

0.384

0.314

0.275

0.382

0.312

0.277

RNN

0.405

0.232

0.203

0.400

0.235

0.203

  1. RNN outperforms other models in this case