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Classification of web content is an interesting and widely pursued field of research in machine learning. Web classification could be done in various ways based upon the criteria chosen. Subjective classification involves classification of web pages based upon the subject to which these pages belong (say history, economics, politics, etc.). Another way of classifying web pages could be based upon...
Clustering is grouping similar data items, features, observations etc. In to cluster. Clustering Problem has been addressed many times as it is one of the important step in data analysis in various application areas. This paper presents an overview of message passing data clustering technique with a goal of providing useful concepts which can be accessible to the community of clustering practitioners...
K-Means has been paid attention to many areas recently, however, it is easy to fall into local optimum and the outliers influence the final results. This paper proposes an improved method for k-means clustering. Different from the traditional k-means algorithms, in our algorithm both intracluster compactness and intercluster separation are considered in our new presented method. A new model is established...
In computer vision system, texture refers to the characteristics of an object that appear on its surface. Texture classification is to classify textures in correct texture groups. The accuracy of texture image classification depends on quality of texture features and classification algorithm used. In this paper, Brodatz texture images are used as an experimental data. Features are extracted from texture...
Fatality due to road accidents are increasing with the increase in population and number of vehicles. Intelligent systems are developed to counter act the loss due to road accidents. The paper proposes one such method to counter the accidents by the implementation of pedestrian detection by the use of LBP histogram and HAAR-like features. LBP histogram are used for cross checking the HAAR-like features...
The classification of the iris image based on feature extraction algorithms like SIFT i.e. Scale-Invariant Feature Transform. The SIFT algorithm helps to retrieve macro features from the iris template. Then the iris images which are stored into the database undergoes SIFT feature extraction technique so that they can be compared with the input image provided to the user. The images which fulfill the...
The k Nearest Neighbour (kNN) method is one of the most popular algorithm in clustering and data classification. The kNN algorithm founds to be performed very efficient in the experiments on different dataset. In this paper, we focus on the classification problem. The algorithm is experienced over Leukemia dataset. Initially three feature selection algorithm Consistency Based Feature Selection (CBFS),...
Feature selection technique has a great importance in Internet traffic classification. Machine learning (ML) algorithms have been generally applied in novel traffic classification. In this paper we provide an overview of three major approaches to classify different categories of Internet traffic: Port based approach, Payload based approach, Statistical-based approach. This paper also explain feature...
According to the characteristics of infrared images of electrical equipment, a new image segmentation method based on wavelet transformation and fuzzy clustering is proposed in this paper. Because image segmentation based on the fuzzy C mean (FCM) clustering algorithm is easy to be affected by the initial clustering center and the clustering number, which often leads to the convergence of results...
In this paper, a hybrid intelligent machine learning technique for automatic classification of brain magnetic resonance images is presented. The proposed multistage technique involves the following computational methods, Otsu's method for skull removal, Fuzzy Inference System for image enhancement, Modified Fuzzy C Means with the Optimized Ant Colony System for image segmentation, Second Order Statistical...
MOOCs have refined the way of teaching where the electronic devices can provide knowledge on the go, which says that knowledge is omnipresent. The connectivism is a technique where the knowledge is contained in the electronic media, which can be delivered as per the requirement. The use of Face detection with Haar based algorithms help to track the current status of the user and perform the teaching...
The data generated from both men and machines are exponentially multiplying the size and the structural definition of the data. Such a voluminous, dynamic and unstructured data termed as Big Data is analyzed and maintained and can be used for various purposes and applications. Big Data is generated from sources like social media, cyber physical system and business entities. This enormous data generation...
Yield prediction is very popular among farmers these days, which particularly contributes to the proper selection of crops for sowing. This makes the problem of predicting the yielding of crops an interesting challenge. Earlier yield prediction was performed by considering the farmer's experience on a particular field and crop. This work presents a system, which uses data mining techniques in order...
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