This clearly confirms the contribution of considering common active interactions between the HTS assays as a dependency factor towards enhancing classification performance.
In particular, the proposed approach helps to increase the classification accuracy, while enhancing classification efficiency by requiring considerably less features.
Some of the applications of pansharpening include improving geometric correction, enhancing certain features not visible in either of the single data alone, changing detection using temporal data sets and enhancing classification [10].
MLP and RBF networks can be used in a double classification in such a way to take advantage from their complementary classification performances (with a confidence parameter to enhance classification rates) as well as from their competitive classification performances [3], MLP are neural global approximators, whereas RBF are neural local approximators [11].
3) that: MLP and RBF networks can be used in a double classification in such a way to take advantage from their complementary classification performances (with a confidence parameter to enhance classification rates) as well as from their competitive classification performances [3], MLP are neural global approximators, whereas RBF are neural local approximators [11].
Fusion-0 represents a method employed in previous studies to enhance classification rates, whereas Fusion-1 represents the novelty of the technique, which is the combination of emotion predictions generated by Fusion-0.
The proposed measure can be also used to derive new features that enhance classification accuracy.
Kim, J., Calhoun, V.D., Shim, E. & Lee, J.H. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.
To enhance classification of variants of uncertain significance (VUS) in the DNA mismatch repair (MMR) genes in the cancer predisposition Lynch syndrome, we developed the cell-free in vitro MMR activity (CIMRA) assay.
In designing fuzzy rule based classification systems (FRBCSs), complex fuzzy rule extraction techniques and tuning membership functions are frequently used to enhance classification accuracy.
Moreover, we demonstrated how this technique can enhance classification accuracy while making the neural network unbiased in terms of view point.
