• Ridhima Dhawan
• -

Abstract: In this paper, few distinctive machine learning algorithm strategies recurrent neural network (RNN), convolutional neural network (CNN) and hierarchical attention network has been used to classify the text and performances has been evaluated. Classification of text was executed on datasets having Frennch, Italian, Germman, and Englishh languages. The execution is entirely based on the Kera’s. It characterizes the time taken by each machine learning algorithm RNN, CNN, HAN for processing the text data and also, it epitomizes the training accuracy and validation accuracy of each machine algorithm on the dataset1, dataset2, dataset3 respectively.

Keywords: Text Classification, RNN, CNN, HAN, Kera’s

"Categorization of text with RNN, CNN and HAN models", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.223-230, November 2018, Available :http://www.jetir.org/papers/JETIRDS06033.pdf

"Categorization of text with RNN, CNN and HAN models", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp223-230, November 2018, Available at : http://www.jetir.org/papers/JETIRDS06033.pdf