Python Natural Language Processing

Challenges

The following are the challenges involved in feature engineering:

• Coming up with good features is difficult and sometimes complex.
• After generating features, we need to decide which features we should select this selection of features also plays a major role when we perform machine learning techniques on top of that. The process of selecting appropriate feature is called feature selection.
• Sometimes, during the feature selection, we need to eliminate some of the less important features, and this elimination of features is also a critical part of the feature engineering.
• Manual feature engineering is time-consuming.
• Feature engineering requires domain expertise or, at least, basic knowledge about domains.