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Exact(6)
There appear many classification methods in the literature.
Many classification methods have been proposed in the literature to tackle this problem.
Data sets in which there are many more observations in one class than another are problematic for many classification methods.
Thirdly, many classification methods are based on the pixels, but when the impact of noise is significant, it can easily lead to wrong classifications.
After the transformation, the target is mapped to the source and one can apply many classification methods such as SVM or k-Nearest Neighbors (k-NN).
The concept that conserved sequences among sequences may be a symbol of functionally similar protein domains underlies many classification methods of protein families.
Similar(54)
As for object recognition, many traditional classification methods have shown attractive performance on a specific sensor (domain) [4 6].
The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods.
For unbalanced data, our approach maintains the balance between sensitivity and specificity more adequately than many other classification methods considered in this study.
The technique of machinery fault diagnosis has been greatly enhanced over recent years with the application of many pattern classification methods.
Although many other classification methods are available, decision trees (DT), rule-based methods such as logistic regression (LogR), linear regression (LR), Naive Bayes (NB), support vector machine (SVM), k-Nearest Neighbor (k-NN), and artificial neural networks (ANN).
More suggestions(14)
many classification algorithms
many classification rules
many classification systems
many classification schemes
many classification yards
many classification cases
many classification trees
many classification situations
many classification societies
many classification fields
many classification techniques
many classification machines
many classification tasks
many classification problems
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