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Then, SVM, Rocchio and Naive Bayes algorithms are used as base classifiers to construct an ensemble classifier, which runs iteratively and exploits margins between positive and negative data to progressively improve the approximation of negative data.
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Hierarchical polynomial networks provide approximation of experimental data.
The biplot provides an optimal approximation of the data matrix by such a two-dimensional structure, in that it displays the singular value decomposition – which gives the rank-two approximation to the data matrix having the smallest mean-squared error.
Most of what I've done has found negative results and it's very hard to continue getting negative data when everyone else is getting positive data".
Negative data ignored?
The data points scattered around the diagonal, indicating a close approximation of the original data.
We have emphasized that a lognormal distribution is a reasonable approximation of the empirical data.
The approximation of data distribution to normality was preliminarily tested.
In Fig. 15, we plot the Guinier approximation of the measured data.
The result was a two-dimensional "map" of the points that represents the best approximation of the similarity data.
Finally, we are interested in providing a solution that produces a reasonable, dimension reduced, approximation of the original data.
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