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The performance of our proposed approach is compared with three competing approaches for augmenting datasets and evaluated using multiple classification algorithms; and the results indicate the superior performance of our proposed method.
A classification model is usually obtained by trying multiple classification algorithms [ 28, 29].
Multiple classification algorithms were applied to this cohort to construct a diagnostic classifier that correctly distinguished between MS and NonMS patients.
Multiple classification algorithms implemented in Partek software (St .Louis, Missouri, USA) were applied to the training set subgroups to construct classifiers that can correctly distinguish between MS and NonMS patients.
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In this study, we tested multiple supervised classification algorithms and their combinations for detecting PICO elements within medical abstracts.
In this study, we tested multiple supervised classification algorithms and their combinations for detecting PICO statements within medical abstracts.
We call it MW-MUSIC for Multicomponent Wideband-MUSIC as it is an extension of the MUSIC (MUltiple SIgnal Classification) algorithm [34 37].
Using the MUSIC (MUltiple SIgnal Classification) algorithm to estimate the angle-of-arrival (AoA), we derive a new asymptotic error variance bound when the transmitted signal can be pre-processed.
In this context, the present study introduces WSF2, a novel web spam filtering framework specifically designed to take advantage of multiple classification schemes and algorithms.
In this paper we propose a resampling strategy for classification algorithms that use multiple subsamples.
Choosing the right feature and classification algorithms for this multiple category classification and prediction is critical.
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