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Table 3 MAE rates for all types of hyperparameter tuning predicting hospital demand 1, 3 or 7 days in advance in case of the batch method for St Mary’s hospital

From: A unified machine learning approach to time series forecasting applied to demand at emergency departments

  

Choosing the best set of hyperparameters based on:

algorithm

days

yesterday

the past

exponential

the average over the

caret

   

n days

moving average

whole training set

 
 

1

14.50

14.38

14.48

14.42

14.34

lm

3

14.80

14.96

14.86

14.95

14.80

 

7

15.11

15.17

15.22

15.33

15.13

 

1

15.97

14.49

15.08

14.46

14.30

gbm

3

15.38

14.63

14.86

14.67

14.53

 

7

15.43

14.79

14.93

14.78

14.86

 

1

14.49

14.34

14.38

14.35

14.48

glmnet

3

14.81

14.79

14.82

14.75

14.77

 

7

14.98

15.11

14.94

15.16

15.09

 

1

15.86

15.47

15.74

15.79

15.42

knn

3

16.13

15.78

15.92

16.02

15.57

 

7

16.70

16.05

16.45

16.52

15.89

 

1

14.62

14.46

14.54

14.79

14.45

rf

3

14.66

14.55

14.54

15.15

14.53

 

7

14.93

14.61

14.62

15.53

14.67