The specialization of each neural network simplifies their structure and improves the classification.
Experimental results show that the proposed algorithm improves the classification performance in monotone classification tasks.
The approach produces new relevant features and improves the classification accuracy.
The modified AHP improves the classification performance not only of the HMM but also of all other classifiers.
Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems.
This method creates a set of descriptive features that improves the classification accuracy of multi-temporal image databases.
The results thereof demonstrate that the positively bowed guide blade improves the classification precision and decreases the particle cut size.
We have previously demonstrated that measuring the shape of the nucleus from cells stained with a nuclear marker using imaging flow cytometry drastically improves the classification of mitotic phases9.
Compared with the object-based unsupervised classification method proposed earlier, the proposed algorithm improves the classification accuracy without increasing computational complexity.
The result clearly reveals that the proposed feature selection algorithm improves the classification accuracy for ELM, Naïve Bayes, and SVM classifiers.
Experiments on several datasets have proven that the combined use of both techniques improves the classification accuracy on 3-class sentiment analysis.
