What are Features?

Features are nothing but the independent variables in machine learning models. What is required to be learned in any specific machine learning problem is a set of these features (independent variables), coefficients of these features, and parameters for coming up with appropriate functions or models (also termed as hyperparameters). The following represents a few examples of what can be termed as features of machine learning models:

A model for predicting whether the person is suitable for a job may have features such as:
*education qualification
* number of years of experience
* experience working in the field etc.

A model for predicting the size of a shirt for a person may have features such as age, gender, height, weight, etc.

Features can be in the form of raw data that is very straightforward and can be derived from real-life as it is. However, not all problems can be solved using raw data or data in its original form.

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