Struct rustlearn::multiclass::OneVsRestWrapper

pub struct OneVsRestWrapper<T> {
    // some fields omitted
}

Wraps simple two-class classifiers to implement one-vs-rest strategies.

Methods

impl<T: Clone> OneVsRestWrapper<T>

fn new(base_model: T) -> OneVsRestWrapper<T>

fn models(&self) -> &Vec<T>

fn class_labels(&self) -> &Vec<f32>

Trait Implementations

impl<T: Decodable> Decodable for OneVsRestWrapper<T>

fn decode<__DT: Decoder>(__arg_0: &mut __DT) -> Result<OneVsRestWrapper<T>, __DT::Error>

impl<T: Encodable> Encodable for OneVsRestWrapper<T>

fn encode<__ST: Encoder>(&self, __arg_0: &mut __ST) -> Result<(), __ST::Error>

impl<'a, T: SupervisedModel<&'a Array> + Clone> SupervisedModel<&'a Array> for OneVsRestWrapper<T>

fn fit(&mut self, X: &'a Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &'a Array) -> Result<Array, &'static str>

fn predict(&self, X: &'a Array) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseRowArray> + Clone> SupervisedModel<&'a SparseRowArray> for OneVsRestWrapper<T>

fn fit(&mut self, X: &'a SparseRowArray, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &'a SparseRowArray) -> Result<Array, &'static str>

fn predict(&self, X: &'a SparseRowArray) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseColumnArray> + Clone> SupervisedModel<&'a SparseColumnArray> for OneVsRestWrapper<T>

fn fit(&mut self, X: &'a SparseColumnArray, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &'a SparseColumnArray) -> Result<Array, &'static str>

fn predict(&self, X: &'a SparseColumnArray) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a Array> + Clone + Sync> ParallelPredict<&'a Array> for OneVsRestWrapper<T>

fn decision_function_parallel(&self, X: &'a Array, num_threads: usize) -> Result<Array, &'static str>

fn predict_parallel(&self, X: &'a Array, num_threads: usize) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseRowArray> + Clone + Sync> ParallelPredict<&'a SparseRowArray> for OneVsRestWrapper<T>

fn decision_function_parallel(&self, X: &'a SparseRowArray, num_threads: usize) -> Result<Array, &'static str>

fn predict_parallel(&self, X: &'a SparseRowArray, num_threads: usize) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseColumnArray> + Clone + Sync> ParallelPredict<&'a SparseColumnArray> for OneVsRestWrapper<T>

fn decision_function_parallel(&self, X: &'a SparseColumnArray, num_threads: usize) -> Result<Array, &'static str>

fn predict_parallel(&self, X: &'a SparseColumnArray, num_threads: usize) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a Array> + Clone + Sync + Send> ParallelSupervisedModel<&'a Array> for OneVsRestWrapper<T>

fn fit_parallel(&mut self, X: &'a Array, y: &Array, num_threads: usize) -> Result<(), &'static str>

impl<'a, T: SupervisedModel<&'a SparseRowArray> + Clone + Sync + Send> ParallelSupervisedModel<&'a SparseRowArray> for OneVsRestWrapper<T>

fn fit_parallel(&mut self, X: &'a SparseRowArray, y: &Array, num_threads: usize) -> Result<(), &'static str>

impl<'a, T: SupervisedModel<&'a SparseColumnArray> + Clone + Sync + Send> ParallelSupervisedModel<&'a SparseColumnArray> for OneVsRestWrapper<T>

fn fit_parallel(&mut self, X: &'a SparseColumnArray, y: &Array, num_threads: usize) -> Result<(), &'static str>