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Decision trees are one of the most widely employed classification models, mainly due to their capability of being properly interpreted and understood by the domain specialist. However, decision-tree induction algorithms have limitations due to the typical recursive top-down greedy search they implement. Such local search may often lead to quality loss while the partitioning process occurs, generating...
In this paper, SAR MT imaging and velocity estimation method is proposed. The validity of this method is verified by numerical simulations. The main idea behind this method is to transform the PE problem to be a SOP problem. The advantages of this method include two main aspects: (i) This method can handle the MT imaging problem for different SAR modes, such as mono-static SAR, bistatic SAR, etc.;...
In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the entropy of age distribution is increasing in time. The procedure of the proposed method involves three stages, namely: 1) Prediction of the...
Divergence measures find application in many areas of statistics, signal processing and machine learning, thus necessitating the need for good estimators of divergence measures. While several estimators of divergence measures have been proposed in literature, the performance of these estimators is not known. We propose a simple kNN density estimation based plug-in estimator for estimation of divergence...
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