The correct answer is: B. feature
A feature is a measurable property or parameter of the data-set. It is a characteristic of an entity that can be used to describe it. Features are used to represent data in a way that is meaningful to the machine learning algorithm.
Training data is the data that is used to train the machine learning algorithm. It is used to learn the relationship between the features and the target variable.
Test data is the data that is used to evaluate the performance of the machine learning algorithm. It is used to measure how well the algorithm has learned the relationship between the features and the target variable.
Validation data is a subset of the training data that is used to prevent overfitting. It is used to measure the performance of the algorithm on data that it has not seen before.
In conclusion, a feature is a measurable property or parameter of the data-set. It is a characteristic of an entity that can be used to describe it. Features are used to represent data in a way that is meaningful to the machine learning algorithm.