We present a hybrid learning algorithm called Learning Algorithm using SEarch Rings (LASER). LASER combines Naive Bayes and 1-Nearest neighbor learners in a multistrategic way. The Naive Bayes and the Nearest Neighbor algorithms seem to compliment each other in their search technique and their bias and present a interesting category of learning algorithms called complimentary learners. LASER us...

Recently machine learning based intrusion detection system developments have been subjected to extensive researches because they can detect both misuse detection and anomaly detection. In this paper, we propose an AdaBoost based algorithm for network intrusion detection system with single weak classifier. In this algorithm, the classifiers such as Bayes Net, Naïve Bayes and Decision tree are us...

K nearest neighbor classifier (K-NN) is widely discussed and applied in pattern recognition and machine learning, however, as a similar lazy classifier using local information for recognizing a new test, neighborhood classifier, few literatures are reported on. In this paper, we introduce neighborhood rough set model as a uniform framework to understand and implement neighborhood classifiers. T...

recently, data collection from seabed by means of underwater wireless sensor networks (uwsn) has attracted considerable attention. autonomous underwater vehicles (auvs) are increasingly used as uwsns in underwater missions. events and environmental parameters in underwater regions have a stochastic nature. the target area must be covered by sensors to observe and report events. a ‘topology cont...

In this paper, we propose a Cellular Edge Detection (CED) algorithm which utilizes Cellular Automata (CA) and Cellular Learning Automata (CLA). The CED algorithm is an adaptive, intelligent and learnable algorithm for edge detection of binary and grayscale images. Here, we introduce a new CA local rule with adaptive neighborhood type to produce the edge map of image as opposed to CA with fixed ...

background breast cancer (bc) is the most common cancer in iranian women. studying the mortality statistics is important to monitor the effects of screening programs or the influence of earlier diagnosis on the burden of this chronic disease. misclassification is still a problem in the iranian death registry data and about 20% of death statistics are recorded in misclassified categories. object...

In this paper is presented the impact of feature selection on the accuracy of Bayes classifier. Six feature selection techniques have been used for feature selection, evaluated and compared using supervised learning algorithm on eight real and three artificial benchmark data. Accuracy of the classifier is influenced by the choice of feature selection techniques. In our experiment, One-R improve...

This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference. QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better local optimum than SAVB in terms of the variational free energy in latent Dirichlet...

Standard FCM algorithm takes the pixel gray-scale information into account only, while ignoring the spatial location of pixels, so the standard FCM algorithm is sensitive to noise. This paper present a pavement image segmentation algorithm based on FCM algorithm using neighborhood information. The presented algorithm introduces neighborhood information into membership function to improve the st...