<P> In an experiment, a variable, manipulated by an experimenter, is called an independent variable . The dependent variable is the event expected to change when the independent variable is manipulated . </P> <P> In data mining tools (for multivariate statistics and machine learning), the depending variable is assigned a role as target variable (or in some tools as label attribute), while an independent variable may be assigned a role as regular variable . Known values for the target variable are provided for the training data set and test data set, but should be predicted for other data . The target variable is used in supervised learning algorithms but not in non-supervised learning . </P> <P> In mathematical modeling, the dependent variable is studied to see if and how much it varies as the independent variables vary . In the simple stochastic linear model y i = a + b x i + e i (\ displaystyle y_ (i) = a + bx_ (i) + e_ (i)) the term y i (\ displaystyle y_ (i)) is the i value of the dependent variable and x i (\ displaystyle x_ (i)) is the i value of the independent variable . The term e i (\ displaystyle e_ (i)) is known as the "error" and contains the variability of the dependent variable not explained by the independent variable . </P> <P> With multiple independent variables, the model is y i = a + b x 1, i + b x 2, i +...+ b x n, i + e i (\ displaystyle y_ (i) = a + bx_ (1, i) + bx_ (2, i) +...+ bx_ (n, i) + e_ (i)), where n is the number of independent variables . </P>

What are the variables that do not change in an experiment called