Prediction of Happiness Score of Countries by Considering Maximum Infection Rate of People by COVID-19 using Random Forest Algorithm
2nd IEEE International Conference on Intelligent Technologies, CONIT 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2029208
ABSTRACT
In this paper, the relationship between COVID-19 Maximum Infection Rate (MIR) and the happiness indicators has been investigated for the prediction of Happiness Score of Countries using Random Forest (RF) algorithm. The per-formance of the proposed algorithm is also compared against five other algorithms such as Linear Regression (LR), Ada Boost Classifier (ABC), K-Nearest Neighbor (KNN), Gaussian Naive Bayes (NB) and Logistic Regression. The comparison of performance includes parameters like training accuracy, testing accuracy and computation time. It is clear from the observation that the proposed approach is superior to others. Then the parameters like MAE, MSE, RMSE, R2 Score, Adjusted R2 Score is calculated. This proposed algorithm can be used for other classification and regression work involving large amount of data with missing values like COVID- 19 datasets. © 2022 IEEE.
Ada Boost Classifier (ABC); COVID-19; Gaussian Naive Bayes (NB); Happiness Index (HI); K-Nearest Neighbor (KNN); Linear Regression (LR); Maximum Infection Rate (MIR); Random Forest (RF); Barium compounds; Classification (of information); Classifiers; Decision trees; Large dataset; Logistic regression; Motion compensation; Nearest neighbor search; Random forests; Sodium compounds; Ada boost classifier; Ada boost classifiers; Gaussian naive baye; Gaussians; Happiness index; Infection rates; K-near neighbor; Linear regression; Maximum infection rate; Naive bayes; Nearest-neighbour; Random forest
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
/
Randomized controlled trials
Language:
English
Journal:
2nd IEEE International Conference on Intelligent Technologies, CONIT 2022
Year:
2022
Document Type:
Article
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