Best classification accuracies and number of features to produce accuracies.
- Minseok Seo (316795)
- Sejong Oh (316796)
Publication date
February 2013
DOIAbstract
<p>Best classification accuracies and number of features to produce accuracies.</p
<p>Best classification accuracies and number of features to produce accuracies.</p
A list of all 64 variables used in the features selection along with the best features of size 15 an...
Comparison of information gain ratio of top features from expert-guided and CellProfiler categories....
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>PCHIP and moving average features classify better than conventional parameters, and slightly bett...
<p>The number of features in the optimal feature set for each dataset and the MCC values obtained by...
Comparison of the classification accuracies of different algorithms and different feature fusion met...
The best accuracy and number of selected minimum features by adaptive HD method.</p
<p>*statistically significantly better (p<0.05, t-test) as compared to the results with the original...
Comparison of classification accuracies of dataset 1 with different classifiers.</p
<p>Classification accuracies without data correction or stratification (original) and the best accur...
The accuracies of the two-class classifications at the four CNR levels for the six classifiers.</p
Comparison of classification accuracies of dataset 2 with different classifiers.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
Comparison of accuracy of best machine-learners on various feature categories.</p
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
A list of all 64 variables used in the features selection along with the best features of size 15 an...
Comparison of information gain ratio of top features from expert-guided and CellProfiler categories....
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>PCHIP and moving average features classify better than conventional parameters, and slightly bett...
<p>The number of features in the optimal feature set for each dataset and the MCC values obtained by...
Comparison of the classification accuracies of different algorithms and different feature fusion met...
The best accuracy and number of selected minimum features by adaptive HD method.</p
<p>*statistically significantly better (p<0.05, t-test) as compared to the results with the original...
Comparison of classification accuracies of dataset 1 with different classifiers.</p
<p>Classification accuracies without data correction or stratification (original) and the best accur...
The accuracies of the two-class classifications at the four CNR levels for the six classifiers.</p
Comparison of classification accuracies of dataset 2 with different classifiers.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
Comparison of accuracy of best machine-learners on various feature categories.</p
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
A list of all 64 variables used in the features selection along with the best features of size 15 an...
Comparison of information gain ratio of top features from expert-guided and CellProfiler categories....
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
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