pub trait Fit<R: Records, T, E: Error + From<Error>> {
type Object;
fn fit(&self, dataset: &DatasetBase<R, T>) -> Result<Self::Object, E>;
}
Expand description
Fittable algorithms
A fittable algorithm takes a dataset and creates a concept of some kind about it. For example in KMeans this would be the mean values for each class, or in SVM the separating hyperplane. It returns a model, which can be used to predict targets for new data.
Required Associated Types§
Required Methods§
fn fit(&self, dataset: &DatasetBase<R, T>) -> Result<Self::Object, E>
Implementors§
source§impl<R: Records, T, E, P: ParamGuard> Fit<R, T, E> for Pwhere
P::Checked: Fit<R, T, E>,
E: Error + From<Error> + From<P::Error>,
impl<R: Records, T, E, P: ParamGuard> Fit<R, T, E> for Pwhere
P::Checked: Fit<R, T, E>,
E: Error + From<Error> + From<P::Error>,
Performs checking step and calls fit
on the checked hyperparameters. If checking failed, the
checking error is converted to the original error type of Fit
and returned.