Experimental Approach for Big Data Analysis using Machine Learning Techniques

Tracking #: 636-1616

Authors:
NameORCID
Masroor ShahORCID logo https://orcid.org/0000-0002-1208-3822


Submission Type: 

Research Paper

Abstract: 

In daily activities generate a large amount of information from many fields, including business, economic, social networking sites, IoT, and store it on different repository or storages, etc. This information becomes important assets for our departments in future decision making. In this paper a simple step by step solution proposed for big data. Also, investigate to find how much machine learning reliable for it. So, a large data set is used for experiment in this work. Sample machine learning techniques examined for data analysis. For classification and prediction performed the XGBoost model. We obtained high accuracy 1.00 % F1 score. This study motivated researchers that machine learning is the best solution for big data analysis.

Manuscript: 

Supplementary Files (optional): 

Tags: 

  • Reviewed

Data repository URLs: 

Date of Submission: 

Monday, May 25, 2020

Date of Decision: 

Tuesday, May 26, 2020

Decision: 

Reject (Pre-Screening)