It selects the bands based on pattern recognition principles for classification tasks, that is, in this case the band selection is treated as a feature selection problem in pattern recognition, using the response of the chosen classifier combined with the SFFS strategy to select the subset of bands that are more relevant from the point of view of classification performance.
Fig. 13 The Ginseng grade classification method based on pattern recognition.
Figure 13 shows the grade classification method based on pattern recognition.
SVM is a supervised multivariate classification algorithm based on pattern recognition.
We recently reported the development of a tumor classification strategy based on patterns of oncogene and tumor suppressor activity as measured by gene expression signatures of each oncogenic pathway [ 14].
As previously discussed, we recently reported a quantitative tumor classification scheme based on patterns of pathway-associated signatures that can better match the complexity of the tumor, and in doing so, identified two subgroups characterized by high levels of HER2 pathway activity [ 14].
Researchers, who study the EEG signals, concentrated more on pattern classification and feature extraction based on event-related potentials [ 8], visual evoked potential [ 9], and mental tasks [ 10].
The GNMM consists of three steps [63, 64]: channel selection based on the GA, pattern classification using multi-layer perceptron (MLP), and rule-extraction based on mathematical programming.
We can generate rules based on these patterns through classification learning that can provide us with more insight to how genes cluster within a genome.
New methods based on mathematical morphology provide a generic, flexible, and automated approach for the definition of indicators based on the classification and mapping of spatial patterns of connectivity from observed or simulated movement and dispersal events.
