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That is, the dimensions of the features are too large but the samples are too few.
TEMPEST is also shown to be well-suited for analyzing three-dimensional effects of reflection from underlying topography during photoresist exposure which can cause variations in the critical dimensions of the features being formed.
Due to the fair conductivity of the bath and the small dimensions of the features, the overvoltage was shown to be uniform within less than one millivolt over the patterned region of the cathode.
After decreasing the dimensions of the features through the SFS, the new feature set is forwarded to the LS_SVM classifier.
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Scanning all tensor ECG signals into a vector greatly increases the dimensions of the feature space.
We compared the performances of estimators for varying number of training samples with different dimensions of the feature space.
Therefore, we can reduce the dimensions of the feature space by only retaining the first few PCs.
Since maximum three dimensions of the feature domain can be plotted, only three features of the feature vectors are shown in this figure.
We can see from the Fig. 2, when use larger dimensions of the feature, the accuracy increase, while when the number of features is over 60, the accuracy increases slowly and it is much stable.
With the increment of prediction accuracy, the complexity of algorithms and the dimensions of the feature vector to represent the protein sequence are also increasing.
In general, this non parametric approach did not overfit training data, so that good generalization could also be obtained using different dimensions of the feature set (see Figure 1).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com