Struct AutoTuner 

pub struct AutoTuner<S, P: ParamKey> { /* private fields */ }

AutoTuner for hyperparameter optimization.

Example

use aprender::automl::{AutoTuner, RandomSearch, SearchSpace};
use aprender::automl::params::RandomForestParam as RF;

let space = SearchSpace::new()
    .add(RF::NEstimators, 10..500)
    .add(RF::MaxDepth, 2..20);

let result = AutoTuner::new(RandomSearch::new(100))
    .time_limit_secs(60)
    .early_stopping(20)
    .maximize(space, |trial| {
        let n = trial.get_usize(&RF::NEstimators).unwrap_or(100);
        let d = trial.get_usize(&RF::MaxDepth).unwrap_or(5);
        // Return cross-validation score
        evaluate_model(n, d)
    });

println!("Best: {:?}", result.best_trial);

Implementations

impl<S, P: ParamKey> AutoTuner<S, P>

where S: SearchStrategy<P>,

pub fn new(strategy: S) -> Self

Create new tuner with search strategy.

pub fn time_limit_secs(self, secs: u64) -> Self

Add time limit in seconds.

pub fn time_limit_mins(self, mins: u64) -> Self

Add time limit in minutes.

pub fn early_stopping(self, patience: usize) -> Self

Add early stopping with patience.

pub fn verbose(self) -> Self

Add verbose progress logging.

pub fn callback(self, cb: impl Callback<P> + 'static) -> Self

Add custom callback.

pub fn maximize<F>(self, space: &SearchSpace<P>, objective: F) -> TuneResult<P>

where F: FnMut(&Trial<P>) -> f64,

Run optimization to maximize objective.

pub fn minimize<F>(self, space: &SearchSpace<P>, objective: F) -> TuneResult<P>

where F: FnMut(&Trial<P>) -> f64,

Run optimization to minimize objective.