Clustering based Interpretation of deep neural networks for correctly or wrongly classified input testing sample. The feedback path of deep neural network reconstruct the cluster centroids belong to the recognition probabilities of the input testing samples. The reconstructed samples gives us qualitative as well as quantitative analysis about the recognition of the feedforward deep neural network. Furthermore, we perform sample interpolation in the feature space of deep neural network.