Struct GeometricWidthDiscretizer 

pub struct GeometricWidthDiscretizer {
    pub columns: Vec<String>,
    pub bins: usize,
    pub mapping: HashMap<String, Vec<(f64, f64, String)>>,
    /* private fields */
}

Uses a geometric progression to determine bin boundaries.

Fields

columns: Vec<String>

bins: usize

mapping: HashMap<String, Vec<(f64, f64, String)>>

Implementations

impl GeometricWidthDiscretizer

pub fn new(columns: Vec<String>, bins: usize) -> Self

pub async fn fit(&mut self, df: &DataFrame) -> FeatureFactoryResult<()>

Fit computes min and max and then generates geometric intervals. Returns an error if any column has non-positive values.

pub fn transform(&self, df: DataFrame) -> FeatureFactoryResult<DataFrame>

Transform applies the geometric-width discretization.

Trait Implementations

impl Transformer for GeometricWidthDiscretizer

fn fit<'life0, 'life1, 'async_trait>( &'life0 mut self, df: &'life1 DataFrame, ) -> Pin<Box<dyn Future<Output = FeatureFactoryResult<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Fit the transformer given a DataFrame.

fn transform(&self, df: DataFrame) -> FeatureFactoryResult<DataFrame>

Transform the input DataFrame, returning a new DataFrame with the transformation applied.

fn is_stateful(&self) -> bool

Returns true if the transformer is stateful (i.e. requires a call to fit before transform can be called).