Sentence examples for supervised learning methodologies from inspiring English sources
Supervised learning methodologies have been proposed as a better alternative to unsupervised models for link prediction [36].
Applications of supervised machine learning methodology continue to grow in the biomedical literature.
In this work, a set of novel regression approaches are proposed for the MSA evaluation, comparing several supervised learning and mathematical methodologies.
A detailed description of the evaluation methodology, supervised learning algorithms used in classification and regression tasks as well as the quality metrics used to evaluate the performance of mCSM are available as Supplementary Material.
More advanced computational methodologies including supervised learning (Shipp et al, 2002) and artificial neural networks have also been used to define subtypes of breast (Seker et al, 2002) and colorectal cancer (Selaru et al, 2002).
To achieve this goal, we present a novel approach, developing a combined supervised and unsupervised learning methodology.
In this work, we propose a supervised machine-learning methodology to assess the accuracy of assigned molecular functions, based on simple topological properties of an organism's draft metabolic network.
These methodologies are popular in the field of supervised learning, where non-random weak learners are often combined to produce a more accurate predictor [ 35].
In this work, the effect of using different parameterizations for inputs in supervised learning algorithms has been thoroughly analyzed by means of a new methodology.
Both LAMDA and LAMDA-FAR algorithms were used in supervised learning mode to classify a historical database obtained from an experimental mapping methodology of an automotive diesel engine operating under several steady state conditions.
The main contribution of this paper is to introduce a general methodology for practical and efficient characterization and reconstruction of stochastic microstructures based on supervised learning.
