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 |