Data mining and machine learning: an Overview of Classifiers

Abstract

At the same time of information age, digital revolution has made necessary using some of technologies to analyze most of essential information. Data mining is a technique to make sense to the available data. The aim of data mining is extracting the information from a vast volume of data and transforming them into a comprehensible form for human. For this purpose, machine learning methods are used to classify data.In this study, we discuss six popular and useful classifiers in the data mining process.

Mobile Crowdsourcing Networks for Sentiment Analysis Challenges

“…This technique provides intelligent decision making and not only is used to study existing samples, but also predicts the future behavior of the same sample. Classification consists of two phases: first the training phase, in which the data set is analyzed and in the second phase the data is tested and the accuracy of the classification pattern is obtained [15]. Text classification, which means assigning text documents based on content to one or more predefined classes, is one of the most important issues in text mining; sorting e-mails or files in a hierarchical order of folders, identifying the subject of the text, searching structure and / or finding documents that are in the user's interest, are among applications of text classification (classification, classification) [16].…”