Crashing Cars

Ken works for NASCAR, developing a machine-learning model to predict whether a car will crash in a race.

He had access to data for thousands of races, with labels indicating whether each car crashed. After studying the available techniques, Ken had several options for building a binary classification model.

Help Ken in choosing which algorithm to use to build his model.

Ken should use Q-learning algorithm to train his model

Ken should use a Decision Tree as his model choice

Ken should use K-nearest neighbors technique to train the model

Ken should use the K-Means algorithm to train the model