<p>Bagging results for support vector machine classification accuracy using 6 features and resampling training/testing data 1000 times. Treatment refers to the labeling of the data where ‘Pre’ and ‘Post’ refer to if the data labels were shuffled before or after vector training.</p
(a) and (b) show the box plot of the five-class classification accuracy with RF and SVM, respectivel...
<p>The leftmost column contains the names of the methods; the rightmost column shows the average acc...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
<p>SVM-MCS-ca – Support Vector Machine with Modified Cuckoo Search optimizer and classification accu...
<p>Data points marked with an ‘x’ are used for training, while points marked as ‘o’ were used for te...
SVM classification accuracy in %, with classification based on smoothed (unsmoothed) data within the...
The aim of this paper is to analyse the phenomenon of accuracy degradation in the samples given as i...
Appropriate training data always play an important role in constructing an efficient classifier to s...
<p>Summary of the labeling accuracy obtained for the training set, for all the discrimination proble...
classification is the problem of identifying a set of categories to a new comments.To improve the ef...
Mislabeled examples affect the performance of supervised learning algorithms. Two novel approaches t...
<p>(A) Classification accuracy, (B) ROC, (C) F-measure, (D) Computational time (sec.)</p
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction ...
Measuring a larger number of variables simultaneously becomes more and more easy and thus widespread...
Practical experience has shown that in order to obtain the best possible performance, prior knowledg...
(a) and (b) show the box plot of the five-class classification accuracy with RF and SVM, respectivel...
<p>The leftmost column contains the names of the methods; the rightmost column shows the average acc...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
<p>SVM-MCS-ca – Support Vector Machine with Modified Cuckoo Search optimizer and classification accu...
<p>Data points marked with an ‘x’ are used for training, while points marked as ‘o’ were used for te...
SVM classification accuracy in %, with classification based on smoothed (unsmoothed) data within the...
The aim of this paper is to analyse the phenomenon of accuracy degradation in the samples given as i...
Appropriate training data always play an important role in constructing an efficient classifier to s...
<p>Summary of the labeling accuracy obtained for the training set, for all the discrimination proble...
classification is the problem of identifying a set of categories to a new comments.To improve the ef...
Mislabeled examples affect the performance of supervised learning algorithms. Two novel approaches t...
<p>(A) Classification accuracy, (B) ROC, (C) F-measure, (D) Computational time (sec.)</p
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction ...
Measuring a larger number of variables simultaneously becomes more and more easy and thus widespread...
Practical experience has shown that in order to obtain the best possible performance, prior knowledg...
(a) and (b) show the box plot of the five-class classification accuracy with RF and SVM, respectivel...
<p>The leftmost column contains the names of the methods; the rightmost column shows the average acc...
Performance of Support Vector Machine, Random Forest, Multilayer perception, and XGBoost classifiers...
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