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In order to find the best model with a reliable performance, constructed models were evaluated and compared in terms of classification accuracy and computational cost.
The performances of the reported architecture were assessed in terms of classification of stress conditions.
We show that the Twitter-specific lexicon is significantly more effective in terms of classification recall and accuracy metrics.
The design of robust data-based fault diagnostic systems can be formulated in terms of classification tasks.
Experimental results indicate that our proposed scheme brings potential improvements in terms of classification accuracy and number of features.
The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy.
An application of both techniques is evaluated on the same case study, giving special emphasis to their performance in terms of classification success and computation time.
Performance of this system is assessed in terms of classification rate and resource requirements for incremental learning of data blocks coming from real-world video data bases.
This paper presents a new ensemble pruning method which highly reduces the complexity of ensemble methods and performs better than complete bagging in terms of classification accuracy.
Our empirical results on three different scales of public databases show promising potential in terms of classification AUC, accuracy, and computational efficiency.
Experimental results show that the proposed method is better than one-versus-one multiconlitron and directed acyclic graph multiconlitron, both in terms of classification effectiveness and computational time.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com