What is overfitting and underfitting ? Why do they occur? How do you overcome them?

There are three parts to this answer. What is overfitting and underfitting Why do they occur How can you overcome both of them. Overfitting is the result of over training the model while underfitting is the result of keeping the model too simple, both leading to high generalization error. Overtraining leads to a more complex…

Why do you need training set, test set and validation set ?

Before any model is built for the problem in hand, the dataset exists as a single entity. One can start learning from entire dataset and use the built models to make predictions on new unseen data. The later part is called generalization in Machine Learning terminology. However, training on entire dataset available would lead to…

Overfitting is a result of which of the following causes :

Less amount of data Simple Model like a linear classifier Complex Model like a classifier of high degree polynomial All of the above Answer – (1), (3) Overfitting generally happens if the model tries to fit everything because it is too complex or there is too less amount of data. When your model performs well on…