pub struct Normalize { /* private fields */ }Expand description
Per-feature z-score normalisation: x ← (x − mean) / std.
Features with zero standard deviation are left unchanged (i.e. the column remains as-is rather than becoming NaN).
Implementations§
Source§impl Normalize
impl Normalize
Sourcepub fn fit(data: &Array2<f64>) -> Self
pub fn fit(data: &Array2<f64>) -> Self
Fit from a single Array2<f64> (all rows visible at once).
Sourcepub fn fit_from_chunks(
iter: &mut NewStreamingIterator,
) -> Result<Self, DatasetsError>
pub fn fit_from_chunks( iter: &mut NewStreamingIterator, ) -> Result<Self, DatasetsError>
Incremental fit over all chunks produced by iter.
Uses Welford’s online algorithm to compute mean and variance in a single pass, consuming (then resetting) the iterator.
Trait Implementations§
Source§impl Transform for Normalize
impl Transform for Normalize
Source§fn apply(
&self,
chunk: StreamingDataChunk,
) -> Result<StreamingDataChunk, DatasetsError>
fn apply( &self, chunk: StreamingDataChunk, ) -> Result<StreamingDataChunk, DatasetsError>
Apply the transformation to
chunk, returning a (potentially new)
chunk. Implementations may mutate in place and return the same chunk,
or allocate a new one.Auto Trait Implementations§
impl Freeze for Normalize
impl RefUnwindSafe for Normalize
impl Send for Normalize
impl Sync for Normalize
impl Unpin for Normalize
impl UnsafeUnpin for Normalize
impl UnwindSafe for Normalize
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T: ?Sized,
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