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It was concluded that MLPNN and kNN used in this study give good accuracy results for classification of emotions.
Open image in new window Fig. 10 Overall performances of MLPNN and kNN classifiers (f) It was concluded that MLPNN and kNN used in this study give good accuracy results for classification of emotions. .
In "Hyperspectral Image Classification via Contextual Deep Learning," Ma et al. examine the applicability of this paradigm to hyperspectral imaging, and report promising results for classification in remote sensing, where this modality is commonly deployed.
In general the results for classification accuracy rate were not significantly better and in some cases even worse.
Table 7 has the comparison results for classification at C level classes in CATH hierarchy (4 classes).
Although for many complex diseases, there have been impressive numbers of genetic regions identified to be associated, the typical results for classification and probability estimation are that the predictive values are only moderate (Gail 2008; Kooperberg et al. 2010).
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Fig. 4 Accuracy result for classification with a NB classifier and a SVM classifer.
According to the average performances, our 3-20-3 3-20-3 3-20-3on model gives the backpropagation classification.
Firstly, the results for each classification built from training datasets are expressed in terms of a classification accuracy rate, which represents the similarity between the pathological clinical diagnosis and the microarray diagnosis [ 14].
Recently, machine learning based techniques have produced promising results for challenging classification problems.
Table 2 reports the results for each classification method.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com