Imagine, you are solving a classification problems with highly imbalanced class. The majority class is observed 99% of times in the training data. Your model has 99% accuracy after taking the predictions on test data. Which of the following is true in such a case?1. Accuracy metric is not a good idea for imbalanced class problems.2.Accuracy metric is a good idea for imbalanced class problems.3.Precision and recall metrics are good for imbalanced class problems.4.Precision and recall metrics aren’t good for imbalanced class problems.

Machine learning (ML) is a branch of artificial intelligence that leverages data to improve computer performance by giving machines the ability to "learn", or improve performance — based on the data.

There are four basic approaches to machine learning: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.