Shirish S. Sane

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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)
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)
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)
Classification of computer users is very useful for assisting them, anticipating their future actions. In addition, it is very useful for making recommendations to a user based on the histories of other users with similar preferences, detecting changes in the behavior of a user, and so on. Several approaches for classifying users are available, however many(More)
  • Ibrahim M. El-hasnony, Hazem M. El Bakry, +15 authors Tapani Raiko
  • 2015
Nowadays, Healthcare is one of the most critical issues that need efficient and effective analysis. Data mining provides many techniques and tools that help in getting a good analysis for healthcare data. Data classification is a form of data analysis for deducting models. Mining on a reduced version of data or a lower number of attributes increases the(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)
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