[D] Classification with Gradient boosting

Classification with Gradient boosting

I am trying to classify objects in urban area, mainly buildings and vegetations. I am using geometric features from lidar data like planarity, linearity verticality, omnivariance, smallest eigenvalues, change of curvatures, sphericity. I have five classes low vegetation, mid vegetation, high vegetation and buildings.and use the radius from [1...12] I did a randomisedsearch to find the parameters, n_estimator=100, learning rate =0.1, min_sample_split=2, min_sample_leaf= 1. The model gets an accuracy of 98%. When i predict the model …

boosting buildings change classification data features five gradient lidar low machinelearning objects urban