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Classification is undoubtedly gaining major importance in the fields of machine learning, pattern recognition genetic engineering and bio medical sciences where it can be used for automated decision making. Mostly these areas contain datasets having large number of dimensions which require some preprocessing. Thus dimension reduction is a preprocessing step(More)
Detection of outliers is one of the data pre-processing tasks. In all the applications, outliers need to be detected to enhance the accuracy of the classifiers. Several different techniques, such as statistical, distance-based and deviation-based outlier detection exist to detect outliers. Many of these techniques use filter method. A wrapper method using(More)
Cloud data centers provide computing infrastructure as a service to their customers on pay per use basis. In virtualized data centers CPU, RAM, storage and bandwidth are allotted to a Virtual Machine (VM) from pool of shared resources. An autonomic consolidation of VMs on appropriate Physical Machine (PM) by achieving performance and saving cost is the key(More)
With the advent of data mining, in many applications the automated decision making systems are used to make fair decision, but there can be discrimination hidden in the decision made by system. Discrimination refers to treating person or entity unfairly based on their membership to a certain group. Discrimination can be observed not only in social sense but(More)
Dimension reduction is the process of keeping only those dimensions in a dataset which are important from the point of view of problem at hand and discarding of the others. This helps to design easily computable algorithms and to increase the performance of classifiers. It has gained importance as a preprocessing step in knowledge discovery and data mining(More)
Most of you might be in the mode of writing examination during this period of the year (Nov-Dec). Wishing you good luck and success for all your examinations and tests. Let us come back with the renewed interest and energy after semester holidays to face the new semester during which most of the final year students will be involved in project or thesis(More)
Classification is one of the commonly used tasks in data mining. Classification accuracy, training time and storage requirement are some of the important issues in the design of the classifiers. Techniques, such as bagging, boosting and ensembles exist to improve accuracy of classifiers. Feature selection and instance selection algorithms are often used to(More)
In Infrastructure as a Service (IaaS) model of cloud computing paradigm, users acquire computing resources such as CPU, memory, storage and network bandwidth from an IaaS provider and these resources are used to deploy and run their applications. Cloud service providers share computing resources of a physical machine by running isolated Virtual Machines(More)