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Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites...
DDoS attacks bring huge threaten to network, how to effectively detect DDoS is a hot topic of information security. Currently, there are some methods designed to detect DDoS attacks, but the detection rate of them is low. Moreover, DDoS detection is easily misled by flash crowd traffic. In this paper, a new method to detect DDoS attacks based on RDF-SVM algorithm is proposed. By considering the importance...
The paper describes the study on the problem of applying classification techniques in medical datasets with a class imbalance. The aim of the research is to identify factors that negatively affect classification results and propose actions that may be taken to improve the performance. To alleviate the impact of uneven and complex class distribution, methods of balancing the datasets are proposed and...
Autonomic nervous system (ANS) is a control system that acts largely unconsciously and regulates bodily functions. An autonomic malfunction can lead to serious problems related to blood pressure, heart, swallowing, breathing and others. A set of dynamic tests are therefore adopted in ANS units to diagnose and treat patients with cardiovascular dysautonomias. These tests generate big amount of data...
Algorithms used in data mining techniques are of great importance in the field of health care, especially in the case of getting patterns or models that are undiscovered in databases. In the area of health care, leukemia affects the blood status and can be discovered by using the Blood Cell Counter (CBC). This study aims to predict the leukemia existence by determining the relationships of blood properties...
This paper designs an algorithm for the moving object recognition based on support vector machine (SVM) in order to identify and classify the moving objects accurately. In view of the advantages of support vector machine in small sample, nonlinear, and high dimensional pattern recognition, a classifier is constructed based on support vector machine (SVM) is constructed. A feature vector is presented...
Aero-engine fault diagnosis plays a crucial role in safe operation and cost-effective maintenance. Early detection and isolation of component faults prior to failure of aero-engines is of utmost importance. This paper applied various classification methods, including Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbors (K-NN) and Linear Discriminant Analysis (LDA), to aero-engine...
The biggest concern of Network is security. Intro find the tricks and tools of the Attackers. Data Mining techniques automatically learn the pattern of the tuples and Intelligent decision are made. Supervised learning methods finds the attack based on previous knowledge and unknown attacks are detected by using Unsupervised learning. Dos, Probe and Normal data are correctly detected by maximum Data...
Owing to its simplicity and flexibility, the decision tree remains an important analysis tool in many real-world learning tasks. A lot of decision tree algorithms have been proposed, such as ID3, C4.5 and CART, which represent three most prevalent criteria of attribute splitting, i.e., Shannon entropy, Gain Ratio and Gini index respectively. These splitting criteria seem to be independent and to work...
Everyday huge amount of information are transferred from one network to another, the information may be exposed to attacks. The information and information system should be protected from unauthorized users. To provide and maintain the Confidentiality and Integrity of the information is a very tedious job so Intrusion Detection plays a very important role. Although various methods are used to protect...
The recent computing trend is producing tons of data every minutes where the amount of imbalanced data is quite high as far as real life data sets are concerned. In practical aspects of data mining, the imbalanced data set is prone to misguide a data mining model. However, data set needs pre-processing before mining. This work focuses on some practical data mining techniques and produces a valid evaluation...
Data mining applications are becoming a more common tool in understanding and solving educational and administrative problems in higher education. In general, research in educational mining focuses on modeling student’s performance instead of instructors’ performance. One of the common tools to evaluate instructors’ performance is the course evaluation questionnaire to evaluate based on students’...
Binary classification is a process of classifying the elements of a data set into two groups on the basis of a classification rule. It is useful and widely applied in many fields: Information Technology, Business, Medical Diagnosis, Finance, and so on. The problems of the previous works do not specify clearly which classifier utilizes to minimize which type of false, False Positive (FP) or False Negative...
Most of the service providers and product based companies while launching brand new products, services or releasing new versions of existent products need to campaign to reach at the potential customers. While doing so they target their already existing customers who are the ambassadors of their company. To address the existing customers, they maintain the detailed customer data at all levels as customer...
Cancer is currently a major cause of death, which resulted in great interest in the mechanisms of this disease, and how to prevent or cure it. Certain cytokines are spotlighted to be a key to solving this problem, since they play a role in the immune system against cancer. Thus, our goal is to analyze various cytokines and to mine their rules. In this study, we aimed to mine a common rule between...
Multi-class imbalanced data classification problem is common in the real world, but traditional binary classification methods cannot be directly applied. Existing solutions include designing new multi-class classification algorithm and dividing multi-class classification problem into binary classification problem. The latter includes two widely used strategies, namely one versus all (OVA) and one...
CHRONIOUS system is an integrated platform aiming at the management of chronic disease patients. One of the most important components of the system is a Decision Support System (DSS) that has been developed in a Smart Device (SD). This component decides on patient's current health status by combining several data, which are acquired either by wearable sensors or manually inputted by the patient or...
Support vector machine (SVM) has been widely used for its outstanding performance. But, it still has flaws. One of them is that SVM is unit sensitive. In this paper, we analyze how will the different units effect the SVM. Then, we propose a preprocess method not only to conquer this flaw, but also improve the generalization precision of SVM. The preprocess method is base on decision tree(DT). The...
Basing on the SVM that is used to solve pattern recognition problems, this paper brings up a new pattern recognition method that combines the kernel K-means Clustering with decision tree SVM. And this method is simpler structure and higher computational efficiency than old one. Meanwhile, this method achieves a good result in the experiment.
Support Vector Machines (SVM), one of the new techniques for text classification, have been widely used in many application areas. SVM try to find an optimal hyperplane within the input space so as to correctly classify the binary classification problem. We present a novel heuristic text classification approach based on genetic algorithm (GA) and SVM. Simulation results demonstrate that GA and SVM...
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