On the other hand, the absence of significant correlations with socio-demographic and individual measures such as gender and parental higher education shows that, unlike TSS which is given high weighting in the admissions process, the aptitude test does not measurably suffer from bias favouring particular groups.
If an algorithm such as the weighted least squares is used, then one-hop links can be given higher weight thus reducing the error.
The knowledge of adaptability includes the adaptability characteristic of old cases returned by the adaptability analysis and the guideline that the training data from adaptable case should be given higher weight to build SVM model.
The methodology is founded on the premise that, absent a consensus on social policy priorities, that are, on which indicators are more important and should be given higher weights in the index, each state is granted leeway for deciding how to weigh its own indicators and the most favorable weights for indicators are determined for each state.
For example, closer electrodes (i.e., configurations 1 4) can be given higher weights than farther electrodes (i.e., configurations 8 10).
A weight, w(t), is given to each term t to quantify its importance (e.g. properties that are rare and/or of particular interest to researchers may be given higher weights).
Therefore, in AdaBoost, the samples in the minority class that are often misclassified at start will be given higher weights in subsequent classifiers and then have higher chance to be correctly classified.
Parameter sets which give rise to distributions which are generated by many other parameter sets will be given lower weight, due to the normalisation factor in this equation, whereas parameter sets that generate results in quartiles for which other parameter sets infrequently produce results will be given higher weights.
It is a biased approach, where prominent features are given high weights to play a major role in choose a sentiment label.
During each iteration, incorrectly classified samples are given high weights so that they will have high chance to be correctly classified in the next iteration.
