Feature Selection: Where Science Meets Art - KDnuggets

Some people say feature selection and engineering is the most important part of data science projects. In many cases it's not sophisticated algorithms, rather it's feature selection that makes all the difference in model performance. For example, if you want to predict house prices, knowing just the number of bedrooms and floor area is not good enough. You are omitting many important variables a buyer cares about such as location, school district, property age etc. You can also come from the other direction and choose 100 different features that describe every tiny detail such as names of trees on the property.