Statistical analysis
MIs
There may be complex and unknown relationships between the dependent and independent variables in the dataset. Discovering and quantifying the degree to which variables in the dataset are dependent upon each other is an important step in machine learning because this information can help us better prepare our data to meet the requirements of ML algorithms. The Pearson correlation coefficient (CC) was calculated between MIs and GPR. The CC ranges were defined to be 0.0 < CC < 0.2 for no correlation, 0.21 < CC < 0.4 for weak correlation, 0.41 < CC < 0.6 for moderate correlation, 0.61 < CC < 0.8 for strong correlation, and CC greater or equal to 0.8 for very strong correlation.Furthermore, one‐way ANOVA was performed to determine whether there are any statistically significant differences among all treatment sites regarding MIs. All statistical analysis was performed using SPSS (Ver.27).