S3 method for printing model results
# S3 method for dorem print(x, ...)
| x | Object of class |
|---|---|
| ... | Extra arguments |
data("bike_score") banister_model <- dorem( Test_5min_Power ~ BikeScore, bike_score, method = "banister", control = dorem_control( cv_folds = 3, cv_repeats = 5, shuffle = TRUE ) )#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>print(banister_model)#> Dose-Response Model using banister method #> Training data consists of 1 predictor and 165 observations #> Coefficients are estimated using L-BFGS-B method with 1000 max iterations and -Inf VTR #> #> The following start and bound values were used: #> #> start lower upper #> intercept 271 0 302 #> BikeScore.PTE_gain 1 0 10000 #> BikeScore.PTE_tau 21 0 300 #> BikeScore.NTE_gain 3 0 10000 #> BikeScore.NTE_tau 7 0 300 #> #> Estimated model coefficients are the following: #> #> intercept BikeScore.PTE_gain BikeScore.PTE_tau BikeScore.NTE_gain #> 266.0204779 0.3020749 33.6433797 0.3514750 #> BikeScore.NTE_tau #> 24.6056388 #> #> Objective function equal to: 2.1939 #> #> Cross-Validation of the model was performed using 5 repeats of 3 folds. Shuffling of the predictors was performed. #> #> Overall model performance using selected estimators is the following: #> #> training CV shuffle #> N 9.00000000 45.000000 9.000000e+00 #> meanDiff 0.01374013 -1.240419 -2.865592e-06 #> SDdiff 1.57096328 6.099774 3.506197e+00 #> RMSE 1.48118212 6.157845 3.305674e+00 #> MAE 1.16731419 3.293757 2.830535e+00 #> minErr -2.71352646 -33.580682 -5.498230e+00 #> maxErr 2.22332820 9.961517 5.207445e+00 #> MAPE 0.40904959 1.139914 9.831404e-01 #> R_squared 0.97975692 0.698462 8.991194e-01