This paper is published in Volume-7, Issue-3, 2021
Area
Data Science
Author
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan
Org/Univ
Anjuman College of Engineering and Technology, Nagpur, India
Keywords
Mode, Median, Mean, Pre-Processing, Outlier, Feature Scaling
Citations
IEEE
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan. An efficient data pre-processing model for machine learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan (2021). An efficient data pre-processing model for machine learning. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan. "An efficient data pre-processing model for machine learning." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan. An efficient data pre-processing model for machine learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan (2021). An efficient data pre-processing model for machine learning. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Piyush Lawatre, Mohammed Muzzammil, Rishabh Hingal, Fatir Khan, Rizwan Khan. "An efficient data pre-processing model for machine learning." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Abstract
Currently, data pre-processing is one of the areas of nice interest as a result of it permits the discovery of hidden and infrequently attention-grabbing patterns in massive volumes of information. information scientists pay most of their time on information preparation tasks that have investigation regarding the info, loading information, and cleanup information, in line with an exploration conducted by Anaconda. The real-world massive information sets square measure obtained from several sources and contain data that tend to be incomplete, creaky, and inconsistent thence required correct investigation. during this context, it’s vital to arrange information to satisfy the necessities of information mining algorithms. this can be the role of the information pre-processing stage, within which information cleanup, transformation, and integration, or information spatiality reduction square measure performed. just about any sort of information analytics, information science or AI development needs some sort of information pre-processing to supply reliable, precise, and strong results for enterprise applications.