Arabic Text ClassificationGstemNeural NetworkDeep LearningNowadays, the volume of data offered on the Internet is growing every moment, and the necessity to analyze these data and convert to useful information increased. There are several types of research exploring techniques to deal with Text ...
You want to label each text with a category, and these categories are mutually exclusive (a text doesn’t belong to two categories at the same time). To consider this, instead of using the ReLu activation function you will use theSoftmaxfunction. This function transforms the ...
Deep learning Recurrent neural network Gated recurrent unit Natural language processing Classification Supervised learning Biomedical text Transformer 1. Introduction Adverse drug reactions(ADRs) are one of the main concerns threatening public health [1]. Adverse drug reactions are any harm or effect caused...
As far as we are aware, there is limited evidence regarding the use of deep learning classifier approach in comparison with other baseline methods to assess concurrent nutritional statuses in children from early childhood through adolescence in Ethiopia. Consequently, this proof-of-concept study seeks ...
This can be attributed to the fact that compared with machine learning algorithms, such as SVMs, deep learning methods, such as CNNs and DNNs, are better equipped to classify higher-dimensional and more complex features. Because they use a shallow learning method, SVMs may suffer from the ...
A deep learning text classification method typically uses a pre-trained feature extractor, \(f(\cdot ; \theta _p)\), and then fine-tunes it along with the classification model using domain-specific datasets. The pre-trained feature extractors are usually transformer-based language models such as...
This paper deals with idiom identification as a text classification task. Pre-trained deep learning models have been used for several text classification tasks; though models like BERT and RoBERTa have not been exclusively used for idiom and literal classification. We propose a predictive ensemble ...
using a supervised learning approach with data collected from wild red deer (Cervus elaphus) in the Swiss National Park. While the accelerometer data collected on multiple axes served as input variables, the simultaneously observed behavior was used as the output variable. Further, we used a variet...
We show how this problem has been expressed in terms of text classification via machine learning. We also show how our approach has been applied to certain real-life projects and we discuss the benefits provided to end users. Introduction In the last few years, the diffusion of web-centric ...
Using the BLAST software locally, accessing a local database allows a fairer comparison in terms of processing time with the deep learning strategy proposed in this work. The same computer used to run BLAST with its database was also used to train and run the CNN strategy. The computer has...