Abstract: Most of the content on various social media platforms has enormous textual data. Before being used in machine learning models, this textual data must be transformed into numerical formats ...
Deep learning methods such as multilayer perceptrons (MLPs) and convolutional neural networks (CNNs) have been applied to predict the complex traits in animal and plant breeding. However, it remains ...
My dataset consists of 2089 patients and each patient has a sequence of time/code pairs of varying length. The time is numeric value relative to a reference date, with values from 0 back to -800 ...
The preprocessing strategies specific to each model are summarized in Table 4. Many machine learning models require one-hot encoding to convert categorical features from text to a numeric format, ...
ABSTRACT: Evaluating drug safety during pregnancy remains an ongoing clinical and pharmacological challenge due to ethical, practical, and regulatory barriers, resulting in scarce human clinical trial ...
Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, United States Center for Computation and Technology, Louisiana State University, Baton Rouge, ...
"0 1.0 0.0 0.0 1.0 0.0 0.0 India 44 72000\n", "1 0.0 0.0 1.0 0.0 0.0 1.0 US 34 65000\n", "2 0.0 1.0 0.0 0.0 1.0 0.0 Japan 46 98000\n", "3 0.0 0.0 1.0 0.0 0.0 1.0 US ...
Abstract: Many cybersecurity logs contain a substantial volume of textual data regarding security events. This data needs to be converted to numerical types before any machine learning (ML) algorithms ...
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