Which of the following is false about most machine learning models?


They require numbers or collections of numbers as input.


They are flexible enough to handle all issues you might see in your dataset (lack of data, incorrect data, etc)


They are trained by iteratively adjusting their parameters to minimize a loss function.


Once trained, their model parameters can be used to make new predictions in a process called a “model inference algorithm.”