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The proposed classifier is compared with a CNN trained with randomly ordered features and Logistic Regression.
Both approaches are based on combining rankings of features that contain all the ordered features.
Experimental results show that the proposed classifier outperforms both Logistic Regression and CNN that utilizes randomly ordered features.
A facile strategy for fabricating hierarchically micro- and nano-scale ordered features as antireflection coating is developed.
Engineered surface topographies, particularly geometries of ordered features designed with unique roughness properties, elicit specific, predictable biological responses and have been shown to control bio-adhesion [27 29].
One way to mitigate this incompatibility problem is to transform the unordered extracted feature sets to ordered feature representation without sacrificing the discrimination power of the original features so that a feature fusion on ordered features can subsequently be applied.
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The first column contains unit vectors, each of which represents a feature in the ordered feature set.
For the genuine user, sort the set from largest to smallest into a sequence of ordered feature indices.
Because each sample was originally represented by a 35-dimensional feature vector based on the mRMR ordered feature list, 35 candidate feature sets were built.
Finally, we can get an ordered feature list with a rank for every feature to indicate its importance in the feature set.
In the IFS procedure, we built 500 feature sets based on the ordered feature set S obtained in the mRMR step.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com