Collinearity is a common problem in medical analysis. For example, age group is classified data, and age is numerical data. If the data is not collinearly processed, it will produce a very high prediction accuracy, but it is meaningless. How will Autoprognosis handle that?
Collinearity is a common problem in medical analysis. For example, age group is classified data, and age is numerical data. If the data is not collinearly processed, it will produce a very high prediction accuracy, but it is meaningless. How will Autoprognosis handle that?