We do not assume data in the target domain follows the same distribution as that in the source domain, and the motivation of our work is to enhance a supervised online learning task on a target domain by exploiting the existing knowledge that had been learnt from training data in source domains.
An improved manifold learning method, called enhanced semi-supervised local Fisher discriminant analysis (ESELF), for face recognition is proposed.
In [18], a semi-supervised approach attempts to enhance the performance of relevance feedback by exploiting unlabeled images, integrating semi-supervised learning and active learning.
After concluding that supervised methods with wrapper selection of variables enhance the classification, the next step was to determine which supervised algorithm was best able to discriminate between pyramidal cells and interneurons in our benchmark test.
To obtain a higher level of group separation and enhance recognition of variables responsible for classification, a supervised PLS-DA was applied.
However, we showed that this defect can be transformed into a merit through combination with supervised classifiers like SVM, where the tuning parameter such as a kernel parameter can be used to enhance sample discrimination in relation to the aim of the supervised task.
Moreover, routine tasks that cause tediousness and boredom can lead to a lack of stimulus and growth in the workplace [ 59], which could be avoided by supervised work plans that are intended to enhance creativity [ 60].
In [14], authors use clustering ensemble for classifiers combination, because the use of cluster analysis techniques in supervised classification tasks has shown that they can enhance the quality of the classification results.
Futhermore, comparative studies have shown the necessity of the proposed scheme as a supervised wide-area backup system for distance protection to enhance the reliability.
Seven bands of the raw image (bands 1 7) were merged to create new raster, enhance radiometry, clipped for the study area, and then classified using supervised maximum likelihood approach by Image Classification tool in ArcGIS 10.2.
