Control charts primarily in the form of X chart are widely used to identify the situations when control actions will be needed for manufacturing systems. Various types of patterns are observed in control charts. Identification of these control chart patterns (CCPs) can provide clues to potential quality problems in the manufacturing process. This paper introduces a novel hybrid intelligent syst...

The dramatically development of internet, Security of network traffic is becoming a major issue of computer network system. Attacks on the network are increasing day-by-day. The Hybrid framework would henceforth, will lead to effective, adaptive and intelligent intrusion detection. In this paper, We propose a hybrid fuzzy rough with Naive bayes classifier, Support Vector Machine and K-nearest n...

With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a n...

This paper presents a method for designing a semisupervised classifier for multi-component data such as web pages consisting of text and link information. The proposed method is based on a hybrid of generative and discriminative approaches to take advantage of both approaches. With our hybrid approach, for each component, we consider an individual generative model trained on labeled samples and...

Subspace learning is very important in today's world of information overload. Distinguishing between categories within a subset of a large data repository such as the web and the ability to do so in real time is critical for a successful search technique. The characteristics of data belonging to different domains are also varying widely. This merits the need for an architecture which caters to ...

For the relevance feedback task, our system uses ranking information of relevant and non-relevant documents from previously submitted runs to the TREC Legal Track to train a classifier. The classifier is applied to the remaining unjudged documents to create a new ranked list. This approach is applied to sets of input runs, including a hybrid run where a classifier trained on one set of runs is ...

One of the major developments in machine learning in the past decade is the Ensemble method, which finds a highly accurate classifier by combining many moderately accurate component classifiers. In this paper, we propose a classifier of integrated neuro-fuzzy system with Adaboost algorithm. It is called Hybrid-neuro-fuzzy system and Adaboost-classifier classifier. Herein, Adaboost creates a col...

Intrusion detection system (IDS) is a system that gathers and analyzes information from various areas within a computer or a network to identify attacks made against these components. This research proposed an Intrusion Detection Model (IDM) for detection intrusion attempts, the proposal is a hybrid IDM because it considers both features of network packets and host features that are sensitive t...

Mean Field Genetic Algorithm (MGA) is a hybrid algorithm of Mean Field Annealing (MFA) and Simulated annealing-like Genetic Algorithm (SGA). It combines benefit of rapid convergence property of MFA and effective genetic operations of SGA. This paper presents an approach for building a multi-classifier system in a MGA-based inductive learning environment. Multiple base classifiers are combined t...

In this paper a hybrid adaptive particle swarm optimization aided learnable Bayesian classifier is proposed. The objective of the classifier is to solve some of the fundamental problems associated with the pure naive Bayesian classifier and its variants with a larger view towards maximization of the classifier accuracy. Further, the proposed algorithm can exhibits an improved capability to elim...