Annex v0.2.0 Annex.Perceptron View Source
A simple perceptron Learner capable of making good predictions given a linearly separable dataset and labels.
Link to this section Summary
Link to this section Types
Link to this type
activation() View Source
Link to this type
data_type()
View Source
data_type()
View Source
data_type() :: Annex.Data.List1D
data_type() :: Annex.Data.List1D
Link to this type
t()
View Source
t()
View Source
t() :: %Annex.Perceptron{
activation: activation(),
bias: float(),
learning_rate: float(),
weights: [float()]
}
t() :: %Annex.Perceptron{ activation: activation(), bias: float(), learning_rate: float(), weights: [float()] }
Link to this section Functions
Link to this function
new(inputs, activation, opts \\ [])
View Source
new(inputs, activation, opts \\ [])
View Source
new(pos_integer(), activation(), Keyword.t()) :: Annex.Perceptron.t()
new(pos_integer(), activation(), Keyword.t()) :: Annex.Perceptron.t()
Link to this function
predict(perceptron, inputs)
View Source
predict(perceptron, inputs)
View Source
predict(t(), Annex.Data.List1D.t()) :: float()
predict(t(), Annex.Data.List1D.t()) :: float()
Link to this function
train(p, dataset, opts \\ [])
View Source
train(p, dataset, opts \\ [])
View Source
train(t(), Annex.Dataset.t(), Keyword.t()) :: struct()
train(t(), Annex.Dataset.t(), Keyword.t()) :: struct()