Comparison Paper on Optimizing Differential Data Collection with Multiple Random Dummies Crowdsensing Mobiles using SVM
In this age of computer science each and every thing becomes intelligent and perform task as human. For that
purpose there are various tools, techniques and methods are proposed. Support vector machine is a model for statistics and
computer science, to perform supervised learning, methods that are used to make analysis of data and recognize patterns.
SVM is mostly used for classification and regression analysis. And in the same way k-nearest neighbor algorithm is a
classification algorithm used to classify data using training examples. In this paper we use SVM and KNN algorithm to
classify data and get prediction (find hidden patterns) for target. Here we use some images nominal data to classify and
discover the data pattern to predict future progress os work, Uses data mining which is use to classify text analysis in future.
Keywords - SVM, KNN, Patterns, Analysis, Classification.