Type Definition linfa_logistic::ValidMultiLogisticRegression

pub type ValidMultiLogisticRegression<F> = LogisticRegressionValidParams<F, Ix2>;

Validated version of MultiLogisticRegression

Trait Implementations

impl<'a, C: 'a + Ord + Clone, F: Float, D: Data<Elem = F>, T: AsTargets<Elem = C>> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, Error> for ValidMultiLogisticRegression<F>

fn fit(
    &self,
    dataset: &DatasetBase<ArrayBase<D, Ix2>, T>
) -> Result<Self::Object>

Given a 2-dimensional feature matrix array x with shape (n_samples, n_features) and an array of target classes to predict, create a MultiFittedLogisticRegression object which allows making predictions. The target classes can have any number of discrete values.

This method returns an error if any of the preconditions are violated, i.e. any values are Inf or NaN, y doesn’t have as many items as x has rows, or if other parameters (gradient_tolerance, alpha) have been set to inalid values. The input features are also strongly recommended to be normalized to ensure numerical stability.

type Object = MultiFittedLogisticRegression<F, C>