Author Archives: Kulwinder Kaur



Kulwinder Kaur

Feature Selection
in Big Data, Data Mining, Machine Learning, Text Mining, Weka

Feature Selection in Data Mining

In Machine Learning and statistics, feature selection, also known as the variable selection is the operation of specifying a division of applicable features for apply in form of the model formation. The center basis after operating an element collection approach so as to the data hold a number attributes. It is an algorithm can be seen as the grouping of a search procedure for proposes original attribute subsets, along with...

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06 Feb 2018
Semi Supervised Learning Algorithms
in Data Mining, Machine Learning, Text Mining, Weka

Semi-Supervised Learning Models

Semi-Supervised is a category of the Machine Learning approaches and create to control of labeled or unlabeled data for instructions, typically small number of labeled data within a long number of unlabeled data. Semi-Supervised learning fall between unsupervised and supervised knowledge. This approach can be used for traffic identification or classification. This capability suggests traffic classification methods. It depends on single precede information to order...

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25 Jan 2018
Machine  Learning Algorithms
in Data Mining, Weka

Machine Learning Techniques

Machine learning focuses on calculations, based on known property learned from the training data. Representation of information instance and purpose evaluate on these instances are part of all machine learning systems. Overview of the assets that the system will perform well on unseen data instances; the situations under which this can be specific are an input object of learning in the subfield of computational learning...

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24 Jan 2018
Scheduling in cloud computing
in Cloud Computing

Job Scheduling Algorithms in Cloud Computing

Min-Min Scheduling The main idea of the Min-Min algorithm is to map each task to resources which can complete the task in the shortest possible time. The min- min algorithm estimates the execution and completion time of each job on each available resources. It is two-phase in the Min-Min algorithm. 1.It calculates the minimum execution time for all tasks. 2.The task with the least execution...

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22 Jan 2018
Scheduling algorithms example
in Cloud Computing

Scheduling Algorithms with Example

 First Come First Serve Algorithm In this algorithm, jobs are executed on the basis of first come and first out. It is easy to understand and implement It’s not having high performance and having high waiting time. Example Shortest Job First (SJF) Shortest job first algorithm is further having two categories i.e. Preemptive and Non-Preemptive. Preemptive SJF in this algorithm when the processes come to...

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20 Jan 2018
Job scheduling in cloud
in Cloud Computing

TYPES OF SCHEDULING ALGORITHMS

Various advancements have been made towards different calculations for designating, scheduling and scaling the assets productively in the cloud. The essential target of scheduling calculation is: execution upgrade and enhancing the nature of administration alongside keeping up the productivity and decency among the employments and decrease the execution cost. Customary Types of scheduling Algorithms calculations are insufficient able to accomplish these destinations. So to overcome...

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12 Jan 2018
Cloud Reports cloud Iaas simulation tool
in Cloud Computing

CloudReports a cloud IaaS Simulation Tool (Setup in Netbeans)

Step 1  Download cloud reports project from the below mentioned link https://sourceforge.net/projects/cloudreportnetbeans/?source=typ_redirect Goto File –> new project –> java application—> CloudReports copy all the “src/main” folder from the zip file to NetBeans project java application  “src” Folder.   Step 2: go to lib folder in NetBeans right click “add jar ” browse all jar provided to you in “cloudreports/bin/dist/lib” in zip file  and then add cloudreport.jar provided in...

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09 Jan 2018
Bagging and Boosting
in Data Mining, Machine Learning, Text Mining, Weka

Ensemble Learning approach in Data Mining

In our day to day life, when crucial decisions are made in a meeting, a voting among the members present in the meeting is conducted when the opinions of the members conflict with each other. This principle of “voting” can be applied to data mining also. In the voting scheme, when classifiers are combined, the class assigned to a test instance will be the one...

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08 Jan 2018
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