Pipeline class abstract

A class that is used to organize data preprocessing stages in a pipeline manner.

Building the pipeline is a fitting stage - it's a preliminary stage where operators extract metadata from the source data passed to Pipeline for future use, no preprocessing happens here.

Once the process method is called, the actual data preprocessing comes to play.

It's normal, when one uses the same data for fitting and processing, like in the example below.

Example:

import 'package:ml_dataframe/ml_dataframe.dart';
import 'package:ml_preprocessing/ml_preprocessing.dart';
Future main() async {
  final dataFrame = await fromCsv('example/dataset.csv', columns: [0, 1, 2, 3]);
  final pipeline = Pipeline(dataFrame, [
    toOneHotLabels(
      columnNames: ['position'],
      headerPostfix: '_position',
    ),
    toIntegerLabels(
      columnNames: ['country'],
    ),
  ]);

  final processed = pipeline.process(dataFrame);
}

Constructors

Pipeline(DataFrame fittingData, Iterable<PipeableOperatorFn> operators, {DType dType})

Takes fittingData to fit preprocessors from operators list in order to use them further for new data of the same source as fittingData via process method.

factory

Properties

hashCode → int

The hash code for this object.

no setter, inherited

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

process(DataFrame dataFrame) → DataFrame

Applies fitted preprocessors to dataFrame and returns transformed data

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited