Struct goko::plugins::discrete::baseline::DirichletBaseline [−][src]
pub struct DirichletBaseline { /* fields omitted */ }
Trains a baseline by sampling randomly from the training set (used to create the tree) This baseline is not realistic.
Implementations
impl DirichletBaseline
[src]
impl DirichletBaseline
[src]pub fn set_sequence_len(&mut self, sequence_len: usize)
[src]
Sets a new maxium sequence length. Set this to be the window size if you’re using windows, the lenght of the test set you’ve got, or leave it alone as the default limit is the number of points in the training set.
We sample up to this cap, linearly interpolating above this. So, the baseline produced is fairly accurate for indexes below this and unreliable above this.
pub fn set_num_sequences(&mut self, num_sequences: usize)
[src]
Sets a new count of sequences to train over, default 100. Stats for each sequence are returned.
pub fn set_prior_weight(&mut self, prior_weight: f64)
[src]
Sets a new prior weight, default 1.0. The prior is multiplied by this to increase or decrease it’s importance
pub fn set_observation_weight(&mut self, observation_weight: f64)
[src]
Sets a new observation weight, default 1.0. Each discrete observation is treated as having this value.
pub fn set_sample_rate(&mut self, sample_rate: usize)
[src]
Samples at the following rate, then interpolates for sequence lengths between the following.
pub fn train<D: PointCloud>(
&self,
reader: CoverTreeReader<D>
) -> GokoResult<KLDivergenceBaseline>
[src]
&self,
reader: CoverTreeReader<D>
) -> GokoResult<KLDivergenceBaseline>
Trains the sequences up.
Trait Implementations
impl Default for DirichletBaseline
[src]
impl Default for DirichletBaseline
[src]fn default() -> DirichletBaseline
[src]
Auto Trait Implementations
impl RefUnwindSafe for DirichletBaseline
impl RefUnwindSafe for DirichletBaseline
impl Send for DirichletBaseline
impl Send for DirichletBaseline
impl Sync for DirichletBaseline
impl Sync for DirichletBaseline
impl Unpin for DirichletBaseline
impl Unpin for DirichletBaseline
impl UnwindSafe for DirichletBaseline
impl UnwindSafe for DirichletBaseline
Blanket Implementations
impl<T, U> Cast<U> for T where
U: FromCast<T>,
impl<T, U> Cast<U> for T where
U: FromCast<T>,
pub fn cast(self) -> U
impl<T> FromCast<T> for T
impl<T> FromCast<T> for T
pub fn from_cast(t: T) -> T
impl<T> Same<T> for T
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
pub fn to_subset(&self) -> Option<SS>
pub fn is_in_subset(&self) -> bool
pub unsafe fn to_subset_unchecked(&self) -> SS
pub fn from_subset(element: &SS) -> SP
impl<V, T> VZip<V> for T where
V: MultiLane<T>,
impl<V, T> VZip<V> for T where
V: MultiLane<T>,