
Performance Evaluation of Different Classifier for Big data in Data mining Industries
Publication year - 2018
Publication title -
journal of engineering and science research
Language(s) - English
Resource type - Journals
ISSN - 2289-7127
DOI - 10.26666/rmp.jesr.2018.1.3
Subject(s) - computer science , big data , data mining , machine learning , classifier (uml) , artificial intelligence , task (project management) , data set , data science , set (abstract data type) , engineering , systems engineering , programming language
Data mining is the set of computational techniques and methodologies aimed to extract knowledge from a large amount of data, by using sophisticated data analysis tools to highlight information structure underlying large data sets. Data scientist and data engineer are facing big challenges today in society because of global increases in the dataset in the industries and sector today. Machine learning methods represent one of these tools, allowing, not only data management but also analysis and prediction operations. Supervised learning, a kind of machine learning methodology, uses input data and products outputs of two types: qualitative and quantitative, respectively describing data classes and predicting data trends. Classification task provides qualitative responses whereas prediction or regression task offers quantitative outputs. In this paper, an attempt has been made to demonstrate how big data can be analyzed, classified and predicted using weka tool in industries.