Mr2DNM: A Novel Mutual Information-Based Dendritic Neuron Model.By employing a neuron plasticity mechanism, the original dendritic neuron model (DNM) has been succeeded in the classification tasks with not only an encouraging accuracy but also a simple learning rule.  This paper proposes a reliable hybrid model which combines a maximum relevance minimum redundancy (Mr2) feature selection technique with DNM (namely, Mr2DNM) for classifying the practical classification problems.  Experimental results suggest that the proposed Mr2DNM outperforms DNM and other six classification algorithms in terms of accuracy and computational efficiency.
Mr2DNM
Mr2DNM: A Novel Mutual Information-Based Dendritic Neuron Model.By employing a neuron plasticity mechanism, the original dendritic neuron model (DNM) has been succeeded in the classification tasks with not only an encouraging accuracy but also a simple learning rule. 
the original dendritic neuron model (DNM)
Mr2DNM: A Novel Mutual Information-Based Dendritic Neuron Model.By employing a neuron plasticity mechanism, the original dendritic neuron model (DNM) has been succeeded in the classification tasks with not only an encouraging accuracy but also a simple learning rule.  This paper proposes a reliable hybrid model which combines a maximum relevance minimum redundancy (Mr2) feature selection technique with DNM (namely, Mr2DNM) for classifying the practical classification problems.  Experimental results suggest that the proposed Mr2DNM outperforms DNM and other six classification algorithms in terms of accuracy and computational efficiency.
Mr2DNM
Mr2DNM: A Novel Mutual Information-Based Dendritic Neuron Model.By employing a neuron plasticity mechanism, the original dendritic neuron model (DNM) has been succeeded in the classification tasks with not only an encouraging accuracy but also a simple learning rule.  This paper proposes a reliable hybrid model which combines a maximum relevance minimum redundancy (Mr2) feature selection technique with DNM (namely, Mr2DNM) for classifying the practical classification problems.  Experimental results suggest that the proposed Mr2DNM outperforms DNM and other six classification algorithms in terms of accuracy and computational efficiency.
Mr2DNM
The obtained optimal feature subset is used to train and test the DNM for classifying five different problems arisen from medical, physical, and social scenarios. 
the DNM