COVID-19 Prediction Website using Django and Machine Learning | Corona Virus Testing Website, Python
In this video, we will show you a coronavirus predictor website, Where you can predict your covid. You are covid positive or nagitive.
This covid-19 predictor application I developed using machine learning. I used his study aimed to build a COVID-19 prediction model by
applying supervised machine learning algorithms. J48 decision tree, random forest, support vector machine, k-nearest neighbors, naïve Bayes,
and artificial neural network were the algorithms used in this study. The most appropriate configurations were
successfully determined through hyperparameter optimization and 10-fold cross-validation. A comparative
analysis was conducted by evaluating each model’s performance in terms of its accuracy, sensitivity,
specificity, and area under ROC curve, using the Google colab research. The results show that random
forest, support vector machine, k-nearest neighbor, and artificial neural network were the best algorithms to
be utilized in building the COVID-19 prediction model. These algorithms yielded 98.84% accuracy, 100%
sensitivity, 97.69% specificity, and 98.84% area under the ROC curve score. The developed models were successfully integrated in the
development of a machine learning-based web application using the Django Framework.
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