emel/ml/logistic_regression
A classification algorithm used to assign observations to a set of two classes. It transforms its output by using the logistic sigmoid function to return a probability value which can then be mapped to the classes.
Functions
pub fn classifier(data: List(#(List(Float), Bool)), learning_rate: Float, error_threshold: Float, max_iterations: Int) -> fn(
List(Float),
) -> Bool
Returns the function that classifies a poin by using the Logistic Regression Algorithm.
Data = [
{[0.0, 0.0], false},
{[0.0, 1.0], false},
{[1.0, 0.0], false},
{[1.0, 1.0], true}
],
LearningRate = 0.01,
ErrorThreshold = 0.1,
MaxIterations = 1000,
F = emel@ml@logistic_regression:classifier(Data, LearningRate, ErrorThreshold, MaxIterations),
F([1.0, 1.0]).
% true