- Basic understanding of traditional machine learning models.
- Feature engineering of data.
Feature engineering of data is the process of extracting the contrasting features of the data. These features define the entirety of certain instance of the data. Feature engineering demands domain knowledge of the data that is being dealt with, and consequently it is applicable in traditional machine learning models.
A contrasting feature of the data contribute minimal to the definition of a particular instance. Hence classifier based on one feature will result weak learner because only one feature can't generalise the overall definition of the data. Data is defined by combination of features, that makes it a unique instance of particular domain. Weak learners fail to classify such a obvious fact.
Consider a classifying task such as predicting cat or a dog from a picture. The defining aspects of these two animals are wideness of mouth, sharpness of claws, size of limbs, shapes of eyes, size of th