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To evaluate the procedure, we built a prototype system and performed experiments.
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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We perform a standard 5-fold cross-validation procedure: we build the classifier on 80% of the training set and evaluate the accuracy on the remaining 20%.
To obtain an efficient neighbor search procedure, we build an inverse index that returns all instances with the same min-hash value in O(1).
In order to test the compression/decompression procedure, we have built a processing pipeline that both samples and reconstructs data from a dataset.
Using the procedure described above we built 1,500 independent CART trees and each one of the 15,476 genes was classified either in class 1 or class 2 by each tree.
Starting with the assumption that a single NGS read (or read pair) must come from one haplotype, we built a procedure for directly observing haplotypes at a local level by examining 2 or 3 adjacent single nucleotide polymorphisms (SNPs) which are close enough on the genome to be spanned by individual reads.
How can we build procedures at the airport surface that prevent delays and collisions while at the same time meeting the increased demand of air traffic?
For example: How can we build procedures at the airport surface that prevent delays and collisions while at the same time meeting the increased demand of air traffic?
The basic PFC3D modeling procedure is as follows: First, we build a soil model with balls randomly distributed; next, we select a certain group of balls that belong to the rock according to the real rock information; and finally, we combine this group of balls to represent the rock gravels.
The procedure discussed above is outlined in the floating chart of Fig. 4. Following the built procedure, we can process all the OCT images we recorded.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com