Mr . M . Govindarajan

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one of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. This paper addresses using an ensemble of classification methods for intrusion detection. Due to increasing incidents of cyber attacks, building effective intrusion(More)
The area of sentiment mining (also called sentiment extraction, opinion mining, opinion extraction, sentiment analysis, etc.) has seen a large increase in academic interest in the last few years. Researchers in the areas of natural language processing, data mining, machine learning, and others have tested a variety of methods of automating the sentiment(More)
Wireless sensor networks had been deployed in the real world to collect large amounts of raw sensed data. However, the key challenge is to extract high level knowledge from such raw data. Sensor networks applications; outlier/anomaly detection has been paid more and more attention. The propose of a classification approach that provides outlier detection and(More)
Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train(More)
Data Mining is the use of algorithms to extract the information and patterns derived by the knowledge discovery in databases process. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. The Verification of handwritten Signature, which is a(More)
Data Mining is the use of algorithms to extract the information and patterns derived by the knowledge discovery in databases process. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. In many data mining applications that address(More)