[−][src]Trait tinguely::model::SupervisedLearn
Required methods
fn predict(&self, input: &T) -> Result<U, ()>
Predict output from inputs.
fn train<'a, 'b>(&'a mut self, input: &'b T, target: &'b U)
Train the model using inputs and targets.
Implementors
impl<T> SupervisedLearn<Matrix<T>, Vector<T>> for LogisticRegression<T> where
T: Real,
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T: Real,
fn predict(&self, x: &Matrix<T>) -> Result<Vector<T>, ()>
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fn train(&mut self, x: &Matrix<T>, y: &Vector<T>)
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impl<T> SupervisedLearn<Matrix<T>, Vector<T>> for LinearRegression<T> where
T: Real,
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T: Real,
fn predict(&self, x: &Matrix<T>) -> Result<Vector<T>, ()>
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fn train(&mut self, x: &Matrix<T>, y: &Vector<T>)
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Train the linear regression model.
Examples
//use tinguely::regression::LinearRegression; //use mathru::algebra::linear::{Vector, Matrix}; //use mathru::optimization::Gradient; //use tinguely::SupervisedLearn; //let optimizer = Gradient::new(0.1, 200); //let mut lin_mod: LinearRegression<f64> = LinearRegression::new(optimizer); //let inputs: Matrix<f64> = Matrix::new(3, 1, vec![2.0, 3.0, 4.0]); //let targets: Vector<f64> = Vector::new_column(3, vec![5.0, 6.0, 7.0]); //lin_mod.train(&inputs, &targets);