Predictive power has always been the main research focus of learning algorithms with the goal of minimizing the test … on sparse learning in order to avoid overfitting which can greatly affect the accuracy of out-of-sample prediction … response whereas even sparse-learning methods can still preserve a high number of attributes in high-dimensional settings and …

learning techniques. Moreover, we proposed a novel NNR (NASNet Random forest) method for feature engineering. The proposed NNR … from these spatial features. The feature set obtained from the data extraction trains machine learning models. Our …