(UMT, Lahore, 2022) Muhammad Wajeeh Ahmed Raza Khan
Long document classification long is a long-time pending problem that was resolved by the GCN Graph Cnvolution Neural Nework which classifies the data without any pre-embedding and has the capabilities of holding global co-occurrence of words that was missing in the traditional DNN model. The only problem is now that model takes a long-time during training and this problem is addressed by optimization of the activation function. The test results reveal that employing the quantitative measurements of LReLU′s modest negative gradient significantly outperforms LReLU and ReLU on problems including the classification of text.