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A new, saw-tooth shape, vernier ratchet topology to overcome minimum feature dependency is realized.
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The minimum feature size for each nanopattern is 100 nm.
We employ a CMI threshold τ to discover feature dependencies.
Topology solution is developed by feature dependencies graph between bridge objects.
Otherwise, the method computes feature class and feature-feature mutual information and selects a feature that has maximum feature class mutual information but minimum feature-feature mutual information.
Feature dependencies are unavoidable for at least two reasons.
SlimPLS is a multivariate feature extraction method which incorporates feature dependencies into calculation.
Typical issues are data redundancy, outliers and feature dependencies [ 2, 3].
A key strength of the present approach is its explicit handling of feature dependencies (Fig. 5).
Second, feature dependencies oftentimes arise from structural properties of natural scenes.
We also found that our model with feature dependencies outperformed a Naive Bayes model which assumes no dependencies between the feature nodes (overall accuracy of Naïve Bayes model was: 88.5±2.1% with sensitivity: 86.9±2.3%, specificity: 90.0±2.7%, and ppv: 89.7±2.6%).
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