Random Forest result

snap
2

Information about the metrics are nicely compiled here:
Accuracy/Precision/Correlation/TruePositive/FalsePositive/TrueNegative/FalseNegative: https://en.wikipedia.org/wiki/Sensitivity_and_specificity

RMSE, Bias and MAE: https://medium.com/human-in-a-machine-world/mae-and-rmse-which-metric-is-better-e60ac3bde13d

Low accuracy can have many reasons:

  • Not enough training samples to effectively make use of the randomization (comments here)
  • Training samples which are not representative for the classes
  • Inhomogenous training samples (one solution here)
  • Not enough feature rasters (comments here)
  • Not enough trees (comments here)
1 Like