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BIOCHEMISTRY OF FASTING – A REVIEW ON METABOLIC SWITCH AND AUTOPHAGY.
Volume - 13 | Issue-1
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ONE-POT ENVIRONMENT FRIENDLY SYNTHESIS OF IMINE DERIVATIVE OF FURFURAL AND ASSESSMENT OF ITS ANTIOXIDANT AND ANTIBACTERIAL POTENTIAL
Volume - 13 | Issue-1
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MODELING AND ANALYSIS OF MEDIA INFLUENCE OF INFORMATION DIFFUSION ON THE SPREAD OF CORONA VIRUS PANDEMIC DISEASE (COVID-19)
Volume - 13 | Issue-1
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INCIDENCE OF HISTOPATHOLOGICAL FINDINGS IN APPENDECTOMY SPECIMENS IN A TERTIARY CARE HOSPITAL IN TWO-YEAR TIME
Volume - 13 | Issue-1
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SEVERITY OF URINARY TRACT INFECTION SYMPTOMS AND THE ANTIBIOTIC RESISTANCE IN A TERTIARY CARE CENTRE IN PAKISTAN
Volume - 13 | Issue-1
EFFICIENT PREDICTION OF TWITTER BOT IN SOCIAL MEDIA USING K- NEAREST NEIGHBORS COMPARED OVER LINEAR REGRESSION WITH IMPROVED ACCURACY
Main Article Content
Abstract
Aim: Efficient prediction of twitter bot in social media using KNN compared over Linear Regression with improved accuracy. Materials and Methods: The KNN (N=10) and Linear Regression Algorithm (N=10) these two algorithms are calculated by using 2 Groups and I have taken 20 samples for both algorithm and accuracy in this work. Results: Based on the Results Accuracy obtained in terms of accuracy is identified by KNN(65.3%)over Linear Regression algorithm(75.9%).Statistical significance difference between KNN algorithm and Linear Regression Algorithm was found to be 0.220 (p<0.05). Conclusion:The Prediction of finding twitter bot in social media KNN when compared with Linear Regression.
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