learning classification
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Methodology of Adaptation of Data Mining Methods for Medical Decision Support: Case Study
White Paper The classification of data helps to make a decision in different types of problems. Machine Learning, Statistical and Neural Network algorithms are applied for efficient data mining. To deal with these... [29 Aug 2009]
A Nonextensive Method for Spectroscopic Data Analysis With Artificial Neural Networks
White Paper The experimental study verifies that there are indeed improvements in the overall performance in terms of classification success and at the size of network compared to other efficient back-propagation... [29 Aug 2009]
New Optimization Methods in Data Mining
White Paper The methods suggested for solution of such important problems as clustering and classification, were recently obtained by the authors in collaboration with members of EURO working group EUROPT. Data mining is a modern... [29 Aug 2009]
Program Evolution for Data Mining
White Paper Unfortunately, the information in these databases increasingly contains signals that have no corresponding classification symbols. It would be useful to automate (learn) not just a part of the... [29 Aug 2009]
Medical Image Classification Using an Efficient Data Mining Technique
White Paper It is an increasingly popular field that uses statistical, visualization, machine learning, and other data manipulation and knowledge extraction techniques aimed at gaining an insight into the relationships and patterns... [29 Aug 2009]
A Semi-Supervised Approach for Web Spam Detection Using Combinatorial Feature-Fusion
White Paper Each example in this classification task corresponds to 100 web pages from a host and the task is to predict whether this collection of pages represents spam or not. This paper describes a machine... [01 Jul 2009]
Improved Spam Filtering by Extraction of Information From Text Embedded Image e-Mail
White Paper For nearly a decade, content based filtering using text classification or machine learning has been a major trend of anti-spam filtering systems. The increase of image spam, a kind of spam in which the... [01 Jul 2009]
Spam Filtering With Several Novel Bayesian Classifiers
White Paper This paper presents spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Locally Weighted learning with Naïve Bayes... [01 Jul 2009]
Relaxed Online SVMs in the TREC Spam Filtering Track
White Paper In particular, they explore the effect of various sliding-window sizes, trading off computation cost against classification performance with good results. The best results with this approach give... [01 Jul 2009]
Relaxed Online SVMs for Spam Filtering
White Paper The former have advocated the use of Support Vector Machines (SVMs) for content-based filtering, as this machine learning methodology gives state-of-the-art performance for text classification. First,... [01 Jul 2009]
Learning Fast Classifiers for Image Spam
White Paper This paper presents features that focuses on simple properties of the image, making classification as fast as possible. Furthermore, they introduce a new feature selection algorithm that selects features for... [01 Jul 2009]
Towards Automating Malware Classification and Characterization
White Paper Here, the paper proposes using machine learning approaches to learn global (i.e.malware intent) and local (i.e.specific functionality) malware properties based on behavioral traces of malware recorded in virtual... [20 Jun 2009]
Rule-Based Anomaly Detection on IP Flows
White Paper Rule-based packet classification is a powerful method for identifying traffic anomalies, with network security as a key application area. This paper exploits correlations between packet and flow level information via a... [29 May 2009]
Large Margin Hidden Markov Models for Automatic Speech Recognition
White Paper Unlike previous discriminative frameworks for ASR, such as maximum mutual information and minimum classification error, the framework leads to a convex optimization, without any spurious local minima. [13 Dec 2008]
Semi-Supervised Learning: A Comparative Study for Web Spam and Telephone User Churn
White Paper This paper compares a wide range of semi-supervised learning techniques both for Web spam filtering and for telephone user churn classification. Semi-supervised learning has the... [28 Nov 2008]
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