Supervised Machine Learning Techniques for Quality of Transmission Assessment in Optical Networks

Let A be an ARE learning algorithm consisting of an RGI method AR that returns a regular expression, followed by a constraint induction method AC- Let .us assume that the method

To carry out this project successfully, the workflow has been divided into 4 categories: Data, Deep Learning, Machine Learning and Handcrafted Features. For the input of these

Another notable work in the identification of Academic Rising Stars using machine learning came in Scientometric Indicators and Machine Learning-Based Models for Predict- ing

Tweets related to this political party tend to be more explicit than the rest, while PSOE shows the highest levels of distrust, both in terms of denotation and connotation.

The recent exponential growing of machine learning techniques (data-mining, deep-learning, manifold learning, linear and nonlinear regression techniques ... to cite but a few) makes

programming language, code quality, quality score, static analysis, open source projects, software

In the framework of supervised classification (discrimination) for functional data, it is shown that the optimal classification rule can be explicitly obtained for a class of

To provide or facilitate high quality learning opportunities and outcomes in specialist subjects for members of, and groups within, the school’s wider local