Comparison of normalized feature range between manual and semi-automatic methods using z-score normalization. The minimum and maximum values are plotted for each feature and segmentation method.</p
There are needs for evaluating rank order-based similarity between different classifiers in feature ...
The histogram distribution shows the number of features within a range of NDR values where each bin ...
There are needs for evaluating rank order-based similarity between different classifiers in feature ...
<p>Radiomic features derived from 3D-Slicer segmentations had significantly smaller and overlapping ...
Features used to determine the reader comprehension of a text with their corresponding normalization...
<p>The different normalization methods applied in this study, and whether or not they account for le...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
This paper presents three different types of normalization methods. Normalization is particularly us...
<p>Comparison between the accuracy rates achieved with the proposed intensity normalization methodol...
The means and ranges of Numerosity Comparison performance (accuracy, RT) in each condition.</p
Comparison of accuracy and feature dimension under different methods based on mRMR.</p
The range of parameter values when the classification accuracy is located in the top 20% based on FS...
<p>Comparison of average classification results of different classifiers without using light intensi...
Comparison of accuracy and feature dimension under different methods based on KCCAmRMR.</p
Comparison of accuracy and feature dimension under different methods based on tree.</p
There are needs for evaluating rank order-based similarity between different classifiers in feature ...
The histogram distribution shows the number of features within a range of NDR values where each bin ...
There are needs for evaluating rank order-based similarity between different classifiers in feature ...
<p>Radiomic features derived from 3D-Slicer segmentations had significantly smaller and overlapping ...
Features used to determine the reader comprehension of a text with their corresponding normalization...
<p>The different normalization methods applied in this study, and whether or not they account for le...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
This paper presents three different types of normalization methods. Normalization is particularly us...
<p>Comparison between the accuracy rates achieved with the proposed intensity normalization methodol...
The means and ranges of Numerosity Comparison performance (accuracy, RT) in each condition.</p
Comparison of accuracy and feature dimension under different methods based on mRMR.</p
The range of parameter values when the classification accuracy is located in the top 20% based on FS...
<p>Comparison of average classification results of different classifiers without using light intensi...
Comparison of accuracy and feature dimension under different methods based on KCCAmRMR.</p
Comparison of accuracy and feature dimension under different methods based on tree.</p
There are needs for evaluating rank order-based similarity between different classifiers in feature ...
The histogram distribution shows the number of features within a range of NDR values where each bin ...
There are needs for evaluating rank order-based similarity between different classifiers in feature ...