Struct ffsvm::Problem

pub struct Problem<V32> { /* private fields */ }

A single problem a SVM should classify.

Creating a Problem

Problems are created via the Problem::from method and match the SVM type they were created for:

use ffsvm::*;
use std::convert::TryFrom;

fn main() -> Result<(), Error> {
    let svm = DenseSVM::try_from(SAMPLE_MODEL)?;

    let mut problem = Problem::from(&svm);

    Ok(())
}

Setting Features

A Problem is an instance of the SVM’s problem domain. Before it can be classified, all features need to be set, for example by:

use ffsvm::*;

fn set_features(problem: &mut DenseProblem) {
    let features = problem.features();
    features[0] = -0.221184;
    features[3] = 0.135713;
}

It can then be classified via the Predict trait.

Implementations

impl<T> Problem<T>

pub const fn solution(&self) -> Solution

After a Problem has been classified, this will hold the SVMs solution.

pub fn probabilities(&self) -> &[f64]

Returns the probability estimates. Only really useful if the model was trained with probability estimates and you classified with them.

pub fn features(&mut self) -> &mut Features<T>

Returns the features. You must set them first and classifiy the problem before you can get a solution.

impl Problem<SparseVector<f32>>

pub fn clear(&mut self)

Clears the Problem when reusing it between calls. Only needed for SparseSVM problems.

Trait Implementations

impl<V32: Clone> Clone for Problem<V32>

fn clone(&self) -> Problem<V32>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<V32: Debug> Debug for Problem<V32>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.