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DOI: 10.14569/IJACSA.2018.091143

Decision Support System for Agriculture Industry using Crowd Sourced Predictive Analytics

Author 1: Remya S
Author 2: Dr.R.Sasikala

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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 11, 2018.

  • Abstract and Keywords
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Abstract: It is really tough to manually examine the raw data. The Datamining strategies are used to detect the applicable information from uncooked data. The data mining algorithms are efficient for retrieving a specific pattern. In Datamining techniques decision trees are the most commonly used methods for predicting the outcome or behavior of a pattern because they can successfully and efficiently visualize the facts. Presently several decision tree algorithms are advanced for predictive analysis. Right here we gathered a dataset for rubberized mattress, from coir board CCRI, and applied the several decision tree algorithms on the data set and as compared every one. Every set of rules gives a completely unique choice tree from the input statistics. This paper focuses in particular on the Fuzzy c4.5 set of rules and compares one-of-a-kind choice tree algorithms for predictive analysis. Here by using predictive analytics, a decision can be made for each rubberized firms.

Keywords: Predictive analytics; coir fiber; fuzzy-C4.5; crowdsourcing

Remya S and Dr.R.Sasikala, “Decision Support System for Agriculture Industry using Crowd Sourced Predictive Analytics” International Journal of Advanced Computer Science and Applications(IJACSA), 9(11), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091143

@article{S2018,
title = {Decision Support System for Agriculture Industry using Crowd Sourced Predictive Analytics},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.091143},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091143},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {11},
author = {Remya S and Dr.R.Sasikala}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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