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A Literature Review on Supervised Machine Learning Algorithms and Boosting Process

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
M. Praveena, V. Jaiganesh
10.5120/ijca2017914816

M Praveena and V Jaiganesh. A Literature Review on Supervised Machine Learning Algorithms and Boosting Process. International Journal of Computer Applications 169(8):32-35, July 2017. BibTeX

@article{10.5120/ijca2017914816,
	author = {M. Praveena and V. Jaiganesh},
	title = {A Literature Review on Supervised Machine Learning Algorithms and Boosting Process},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {8},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {32-35},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume169/number8/28007-2017914816},
	doi = {10.5120/ijca2017914816},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Data mining is one amid the core research areas in the field of computer science. Yet there is a knowledge data detection process helps the data mining to extract hidden information from the dataset there is a big scope of machine learning algorithms. Especially supervised machine learning algorithms gain extensive importance in data mining research. Boosting action is regularly helps the supervised machine learning algorithms for rising the predictive / classification veracity. This survey research article prefer two famous supervised machine learning algorithms that is decision trees and support vector machine and presented the recent research works carried out. Also recent improvement on Adaboost algorithms (boosting process) is also granted. From this survey research it is learnt that connecting supervised machine learning algorithm with boosting process increased prediction efficiency and there is a wide scope in this research element.

References

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Keywords

Data mining, machine learning, research, adaboost, support vector machine, decision trees.