Calculating Accuracy, Recall and Precision for Logistic Regression Model using PySpark(DataBricks)

Accuracy, Recall and Precisions are important metrics to validate the outcomes of machine learning models. In this model, I am defining accuracy, recall and precision and showing a simple method to calculate them for validating the prediction of Logistics regression model. We shall use these metrices again in the upcoming classification machine learning algorithms as well. If you like to watch logistic regression demo, please visit following link. https://www.youtube.com/watch?v=tUNzWNn5mUo&t=264s If you want to understand dataset used in the demo, use following link. https://www.youtube.com/watch?v=XkzqmpZq7ro&t=168s You can download the code files through git repository using following link. https://github.com/Muhammads786/SQLMachineLearningAlgorithms.git