Context-dependent conclusions are usually driven by empirical observations concerning both the classifier used and the imbalance degree.
Interestingly, even in case of high amounts of benign background (up to 80% dilution), the classifier used by Chudova et al (2010) correctly recognised thyroid malignancy in the majority of their investigated FNA samples.
BioTextRetriever also organizes the papers selected as relevant by the classifier using a ranking function.
Figure 4c shows that mouse samples were nicely clustered according to their predicted subtypes, which were determined by the classifier using approximately 1,000 genes, demonstrating the expression similarity within each subtype and obvious differences between subtypes.
In general, the classifier function is not known a priori and has to be learned by training the classifier using examples (training data).
Additionally, each food source stores its quality (fitness), which is given by the accuracy of the classifier using the feature subset indicated by the bit vector.
For this purpose, we have evaluated the WDO value obtained by the separation algorithm when the classifier uses different sizes of the time-frequency footprint, varying Nfreqs and Nframes from 0 to 6 independently, using the features defined in SET2.
The comparison is performed in terms of the avarage WDO value obtained by the separation algorithm when the classifier uses each set of features, using the database of speech and noise mixtures previously described, with SNR of 0, 3, and 5 dB.
We didn't apply a feature selection method, since this number of features can easily be handled by the SVM classifier used in our experiments.
The introduction of the weighting by w is inspired by the weighted Bayesian classifier used in [14].
