A python implementation of learning and practicing data visualization with a custom Delaware covid dataset that I made during the COVID-19 pandemic. This dataset has the data of Covid cases throughout Delaware, Maryland, Texas and California. A machine learning algorithm, SVR and K-Means Algorithm is trained on the Delaware dataset as I could not get the Maryland, Texas and California datasets to work.
SVR, also known as support vector regression, is a machine learning algorithm used for regression analysis. SVR Model in Machine Learning aims to find a function that approximates the relationship between the input variables and a continuous target variable while minimizing the prediction error. Running my svr model on the Delaware Data and its infections gave an accuracy of 84%, which indicates the model fits the data very consistent.
K-Means Algorithm is an machine learning algorithm, an unsupervised learning algorithm used for data clustering, which groups unlabeled data points into groups or clusters.
Running K-Means Algorithm on the Delaware Dataset based on the number of infections acquired as well as
the increases of infections per day within Delaware
- Python 3
- Seaborn
- Pandas
- Sckit-Learn
- Numpy
- Matplotlib