background mycobacterium tuberculosis genotyping can effectively improve tuberculosis (tb) control programs by controlling disease transmission. pulsed field gel electrophoresis (pfge) is a particularly powerful tool for determination of clonal identity of bacteria providing information for understanding and controlling the spread of disease. objectives the aim of present study was to investiga...

Catastrophic forgetting is a stability–plasticity imbalance that causes machine learner to lose previously gained knowledge critical for performing task. The occurs in transfer learning, negatively affecting the learner’s performance, particularly neural networks and layered learning. This work proposes complementary learning technique introduces long- short-term memory reduce negative effects ...

This paper describes the integration of a learning mechanism called complementary discrimination learning with a knowledge representation schema called decision lists. There are two main results of such an integration. One is an eecient representation for complementary concepts that is crucial for complementary discrimination style learning. The other is the rst behaviorally incremental algorit...

As various types of biomedical data become available, multiple kernel learning approaches have been proposed to incorporate abundant yet diverse information collected from multiple sources (or views) to facilitate disease prediction and pattern recognition. Although supervised multiple kernel learning has been extensively studied, until recently, only a few unsupervised approaches have been pro...

assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. sspco optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. one of the things that smart algorithms are applied to solve is the problem ...

The classification of big data usually requires a mapping onto new clusters which can then be processed by machine learning algorithms means more efficient and feasible linear separators. Recently, Lloyd et al. have advanced the proposal to embed classical into quantum ones: these live in complex Hilbert space where they get split linearly separable clusters. Here, ideas are implemented enginee...