RegressionProblem.md (1122B)
1 # Regression Problem 2 3 ML L1 4 5 **Definition:** A regression problem is a problem where the value trying to be predicted is continuous (think graphing not yes/no). 6 7 Yes/no problem is a [ClassificationProblem](ClassificationProblem.md) 8 9 Also see for a more specific example [LinearRegression](LinearRegression.md) There are other types of regression as well such as polynomial regression (no note at this time). 10 11 When discussing regression, we often use the term "target" instead of "label" to describe the desired output. This contrasts with classification problems where we use the term label. 12 13 See also [LogisticRegression](LogisticRegression.md) where we assign a probability of group membership. 14 15 With regression, we describe the performance measure as the utility function or fitness function. This measures how good the model is. The inverse of this is the cost function which measures how bad it is. 16 17 A uninvariate regression problem is one where you are trying to predict a single value as the output. The opposite of this is a multivariate regression problem where you are trying to detemine multiple output values.