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With the hold-out-sample method, we excluded a subset of the calls, which then had to be classified by the rest of the sample; 62.3% (63.4% including males) were correctly classified confirming that a random sample was possible to assign individually to the trained sample.
The third sample (trained 4 months + 68 km run) was collected 24 hours after the trained sample, and within 30 minutes after the 68 km long sled pulling activity.
Form tunnel boundaries using a trained sample and averaged frame parameters.
where q=1 means that the trained sample is a positive sample of the current class, q=−1 indicates negative samples, w is a weight vector for the model, and b is a bias term.
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Therefore, suppose there are n training sample and each training sample contains six values of economic indicators.
Additional voting by input training samples in reverse order.
Given a training sample matrix X ∈ R m × n which is made up of nm-dimensional training samples, assume that sufficient training samples belonging to the kth class.
Each training sample contains a class label.
(w, c(w)) is a training sample, and D is the set of all training samples.
The set is then treated as the initial training sample.
Suppose a training sample x and the corresponding label y.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com