pub fn preliminary_iter(mut self, num_iter: usize) -> Self {
        self.preliminary_iter = Some(num_iter);

        self
    }
/// Set the number of iterations after which the true P distribution is used
///
/// At the beginning of the training process it is useful to multiply the P distribution values
/// by a certain factor (here 12x) to get the global view right. After this number of iterations
/// the true P distribution value is used. If None the number is estimated.
Set the number of iterations after which the true P distribution is used
At the beginning of the training process it is useful to multiply the P distribution values
by a certain factor (here 12x) to get the global view right. After this number of iterations
the true P distribution value is used. If None the number is estimated.
Set the number of iterations after which the true P distribution is used At the beginning of the training process it is useful to multiply the P distribution values by a certain factor ( here 12x ) to get the global view right . After this number of iterations the true P distribution value is used . If None the number is estimated .
pub fn preliminary_iter(mut self, num_iter: usize) -> Self {
        self.preliminary_iter = Some(num_iter);
        self
    }
pub fn preliminary_iter ( mut self , num_iter : usize ) -> Self { self . preliminary_iter = Some ( num_iter ) ; self }
Set the number of iterations after which the true P distribution is used
At the beginning of the training process it is useful to multiply the P distribution values
by a certain factor (here 12x) to get the global view right.
Set the number of iterations after which the true P distribution is used At the beginning of the training process it is useful to multiply the P distribution values by a certain factor ( here 12x ) to get the global view right .
mut self
num_iter
usize
mut self
num_iter
usize