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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
PREDICTION OF TITANIC DATA ANALYSIS USING LOGISTIC REGRESSION COMPARED WITH NAIVE BAYES FOR BETTER ACCURACY
Main Article Content
Abstract
Aim: The main aim of the research is to predict the survival of passengers on the titanic data analysis using Logistic Regression (LR) over Naive Bayes (NB) machine learning algorithm. Materials and Methods: Logistic Regression and Naive Bayes are implemented in this research work. Sample size is calculated using G - power software and determined as 10 per group with pretest G -power 80%, threshold 0.05% and CI 95%. Result: Logistic Regression provides a higher of 92.94% compared to Naive Bayes algorithm with 88.95% in predicting titanic data analysis. There is a significant difference between two groups with a significance value of 0.004 (p<0.05). Conclusion: Logistic Regression algorithm predicts better information about titanic data analysis than Naive Bayes algorithm.
