Sequential class

A Network model in which every Layer has one input and one output tensor.

Constructors

Sequential({required double learningRate, List<Layer>? layers})
Creates a Sequential model network.

Properties

hashCode → int
The hash code for this object.
no setterinherited
layers → List<Layer>
The Layers part of this Network.
finalinherited
learningRate ↔ double
The degree of radicality at which the Network will adjust its Neurons weights.
getter/setter pairinherited
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
stopwatch → Stopwatch
Used for performance analysis as well as general information logging.
finalinherited

Methods

addLayer(Layer layer) → void
Adds a Layer to this Network.
inherited
addLayers(List<Layer> layers) → void
Adds a list of Layers to this Network.
inherited
clear() → void
Clears the Network by removing all Layers, thereby returning it to its initial, empty state.
inherited
noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
process(List<double> inputs) → List<double>
Processes the inputs by propagating them across every Layer. and returns the output.
inherited
propagateBackwards(List<double> input, List<double> expected) → void
Performs the backpropagation algorithm by comparing the observed values with the expected values, and propagates each layer using the knowledge of the network's 'cost', which indicates how bad the network is performing.
inherited
toString() → String
A string representation of this object.
inherited
train({required List<List<double>> inputs, required List<List<double>> expected, required int iterations, bool quiet = false}) → void
Trains the network using the passed inputs, their respective expected results, as well as the number of iterations to make during training.
inherited

Operators

operator ==(Object other) → bool
The equality operator.
inherited