Assertion: parameter's value | /r/HasProperty | equal
Facets:
value: to β
type: OTHER
value: to 2^(max_depth
type: OTHER
value: ideally
type: DEGREE
Source sentences:
text: Thus, if we enter the y axis at , the corresponding value of will be equal to .
text: Ideally, the value of num_leaves should be less than or equal to 2^(max_depth).
text: {\widehat {\beta }}} is an ordinary least squares estimator in the classical linear regression model (that is, with normally distributed and homoscedastic error terms), and if the true value of the parameter β is equal to β 0 , then the sampling distribution of the t-statistic is the Student's t-distribution with (n − k) degrees of freedom, where n is the number of observations, and k is the number of regressors (including the intercept)[citation
text: If the true value of the parameter β is equal to β 0 and the quantity s .