Table 5 The models’ performance in the context of balanced data.

From: Forecasting solar energetic particles using multi-source data from solar flares, CMEs, and radio bursts with machine learning approaches

Dataset

Models

F1_score

POD

FAR

TSS

HSS

Sweep frequency (balance)

dtree

0.94(±0.01)

0.98(±0.01)

0.1(±0.03)

0.87(±0.03)

0.87(±0.03)

 

RF

0.95(±0.01)

0.98(±0.01)

0.06(±0.02)

0.91(±0.03)

0.91(±0.03)

 

svm

0.96(±0.01)

0.97(±0.02)

0.05(±0.02)

0.91(±0.03)

0.91(±0.03)

 

linsvm

0.94(±0.01)

0.96(±0.02)

0.07(±0.03)

0.88(±0.02)

0.88(±0.02)

Fixed frequency (balance)

dtree

0.95(±0.006)

0.97(±0.01)

0.07(±0.008)

0.89(±0.01)

0.89(±0.01)

 

RF

0.96(±0.008)

0.98(±0.009)

0.05(±0.01)

0.92(±0.01)

0.92(±0.01)

 

svm

0.96(±0.01)

0.97(±0.01)

0.04(±0.01)

0.93(±0.03)

0.93(±0.03)

 

linsvm

0.93(±0.01)

0.97(±0.01)

0.09(±0.01)

0.86(±0.01)

0.86(±0.01)