Table 2.

Key characteristics of machine learning, organized by feature

Feature	Machine learning characteristics	Logistic regression characteristics
Knowledge of predictors	Little a priori knowledge of predictors needed	Requires knowledge of predictors for elimination of unimportant variables from model
No. of predictors	Fewer restrictions on number of predictors in machine learning	Number of predictors is restricted based on number of data points available
Nonlinear relationships	Capable of capturing complex, nonlinear relationships	Has difficulty with modelling nonlinear relationships
Algorithm variety	A host of machine learning algorithms exist, each with its own separate advantages and disadvantages. In addition, additional variations to enhance performance (e.g., bagging, boosting, stacking) may also be used in machine learning.	Multiple types of logistic regression models exist, but models generally have a similar foundation