Table 3.
R2 scores of the best model on the test set for: linear regression, ridge regression, kernel ridge regression, Bayesian ridge regression, lasso regression, support vector machine (SVM), K nearest neighbors (KNN), Gaussian processes (GP), decision tree (DT), random forests (RF), and gradient boosting (GB), for each cosmological parameter.
| Linear | Ridge | k. ridge | b. ridge | Lasso | SVM | KNN | GP | DT | RF | GB | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| H0 | 0.16 | 0.17 | 0.17 | 0.17 | 0.18 | 0.16 | – | 0.16 | 0.05 | 0.15 | 0.16 |
| ωb | – | – | – | – | – | – | – | – | – | – | – |
| ΩM | 0.61 | 0.61 | 0.61 | 0.61 | 0.61 | – | 0.31 | 0.61 | 0.19 | 0.49 | 0.55 |
| ΩΛ | 0.61 | 0.61 | 0.61 | 0.61 | 0.61 | – | 0.31 | 0.60 | 0.19 | 0.49 | 0.55 |
| w0 | 0.65 | 0.65 | 0.65 | 0.65 | 0.65 | 0.57 | 0.49 | 0.65 | 0.42 | 0.59 | 0.60 |
| ns | 0.16 | 0.16 | 0.16 | 0.16 | 0.16 | – | – | 0.16 | 0.02 | 0.10 | 0.11 |
| σ8 | 0.56 | 0.56 | 0.56 | 0.56 | 0.56 | – | 0.30 | 0.56 | 0.25 | 0.48 | 0.49 |
Notes. The dash represents a negative value of the score. The dataset used is the AVG100 with θs = 2′. All models tending to the linear regression obtained the same score, with the exception of support vector machine. Overall, the best score is obtained with the linear regression.
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