Naive Bayes (NB) classifier is a simple and efficient classifier, but the independent assumption of its attribute limits the application of the actual data. This paper presents an approach called particle swarm optimization-naive Bayes (PSO-NB) which takes advantage of combination particle swarm optimization with naive Bayes for attribute selection to improve naive Bayes classifier. This method...

Neighborhood preserving embedding (NPE) is an important linear dimensionality reduction technique that aims at the local manifold structure. NPE contains three steps, i.e. , finding nearest neighbors of each data point, constructing weight matrix, and obtaining transformation matrix. Liang et al . proposed a variational quantum algorithm (VQA) for [ Phys. Rev. A 101 032323 (2020)]. The consists...

Neighborhood algorithm is an important part of 3D SOM algorithm. We proposed three kinds of neighborhood shape and two kinds of neighborhood decay function for threedimensional self-organizing feature maps (3D SOM) algorithm and applied them to three-dimensional image compression coding. Experimental results show that the 3D orthogonal cross neighborhood shape and exponential function algorithm...

although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. but, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. this paper considers the problem of scheduling no-idle hybrid flow shops. a mixed integer linear programming model is first developed to mathematically form...

To improve the positioning accuracy and robustness of indoor positioning technology, a fingerprint positioning method is proposed based on the Kalman filter and the probability weighted Bayes algorithm. Firstly, the optimal estimation of signal strength is calculated using the prediction and correction model of Kalman filter, and then the position is estimated using the posterior probability we...

Main methods, algorithms and applications of the Variable Neighborhood Search metaheuristic are surveyed, in view of a chapter of the Encyclopedia of Optimization.

Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorithms have been proposed to improve naive Bayes, among which tree augmented naive Bayes (TAN) [3] achieves a significant improvement in term of classification accuracy, while maintaining efficiency and model simplicity. I...