Assertion: regression's variable | /r/HasProperty | continuous
Facets:
value: usually
type: DEGREE
value: in nature
type: LOCATION
value: in dependent variable
type: OTHER
value: at the point
type: TEMPORAL
value: with meaningful metric
type: OTHER
value: with intrinsic ordering
type: OTHER
value: in this technique
type: OTHER
Source sentences:
text: In this technique, the dependent variable is continuous, independent variable(s) can be continuous or discrete, and nature of regression line is linear.
text: In this technique, the dependent variable is continuous, independent variable(s) can be continuous or discrete, and nature of regression line is linear.
text: The independent variables can be continuous or binary.
text: Regression discontinuity design requires that all potentially relevant variables besides the treatment variable and outcome variable be continuous at the point where the treatment and outcome discontinuities occur.
text: Scale: variables that are continuous with intrinsic ordering and meaningful metric (
text: Linear regression models deal with variables that are continuous.
text: We identify problem as classification problem when independent variables are continuous in nature and dependent variable is in categorical form i.e. in classes like positive class and negative class.
text: Logistic regression measures the relationship between a categorical dependent variable and one or more independent variables, which are usually continuous, by using probability scores as the predicted values of the dependent variable.
text: Linear regression analysis rests on the assumption that the dependent variable is continuous and that the distribution of the dependent variable (Y) at each value of the independent variable (X) is approximately normally distributed.
text: Regressions use for continuous and categorical variables