A company has build a kNN classifier that gets 100% accuracy on training data. When they deployed this model on client side it has been found that the model is not at all accurate. Which of the following thing might gone wrong? Note: Model has successfully deployed and no technical issues are found at client side except the model performance

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.