comparing cart with backpropagation neural networks in vegetation greenness classification
This paper provides a comparison of CART with BNNs for vegetation greenness classification in terms of classification error rate, computational time, and predicator importance. The experiments were conducted on climatic data and NDVI data. The results show the training time of CART is much less than that of BNNs which achieves better prediction accuracy.
neural networks vegetation classification trees remote sensing