> How do you know you are overfitting? You should test your model on a part of a dataset that it has not been trained upon. You divide your dataset into `train

> How do you know you are overfitting? You should test your model on a part of a dataset that it has not been trained upon. You divide your dataset into `train´ and ´test´. You develop your model on the ´train´ part and check its predictive power on the ´test´ part and compare it to the predictive power on the ´train´ part. IF, the predictive power on the ´train´ part is very good but it performs poorly on the ´test´ part - it is likely that your model is overfitting viz. it has little generalization power and can only do good on ´train´ part of the data. In order to be more sure, you can repeat this process by dividing your dataset into different ´train´ and ´test´ sets. This is called cross validation.