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Chronic Kidney Disease Prediction based on Blood Potassium Levels using Machine Learning
S.D.Harish1, K.Vinay Kumar2, K.Taraka Ram3, G.Pradeepini4

1S.D.Harish*, CSE Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India.
2K.Vinay Kumar, CSE Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India.
3K.Taraka Ram, CSE Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India.
4G.Pradeepini, CSE Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India. 

Manuscript received on November 16, 2019. | Revised Manuscript received on 25 November, 2019. | Manuscript published on December 10, 2019. | PP: 4194-4199 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7113129219/2019©BEIESP | DOI: 10.35940/ijitee.B7113.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Real world problems can be analyzed and solved effectively and efficiently by observing the environment and its phenomenon. We can analyze the nature of the problem by looking for a solution in the environment. The evolution of such systematic handling of the problematic scenario to find an amicable and efficient solution can be applied to real world physical problems. Thus the application of procedures (algorithms) by different species has evolved into a novel idea referred as Nature Inspired Algorithms. It has gained wider publicity and popularity in the present research. One of the most popular nature inspired algorithm which has grabbed the attention of the world is Firefly Algorithm (FA).The Firefly Algorithm has a wide range of applicability in different disciplines. We tried to compare this algorithm along with its variants. We also throw some light on various characteristics of the Firefly Algorithm that makes it a far more efficient algorithm when compared to the rest of such similar algorithms. 
Keywords: Security, Firefly, Problem Identification, Problem Solving, Performance analysis.
Scope of the Article: Machine Learning