SimonAB

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SimonAB

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SimonAB

"""
This function takes a dataframe and a column name (as symbol), and 
prints out the count and the proportion of items within that column.
"""
using DataFrames, Query
function counter(df::DataFrame, col::Symbol)
    for level in unique(df[!, col])
        t = df |> 
            @filter(_[col] == level)|>
            DataFrame    

SimonAB

"""
This function uses gradient descent to search for the weights 
that minimises the logit cost function.

A tuple with learned weights vector (θ) and the cost vector (𝐉) 
are returned.
"""
function logistic_regression_sgd(X, y, λ, fit_intercept=true, η=0.01, max_iter=1000)
    
    # Initialize some useful values

SimonAB

"""
    lin_reg_grad_descent(X, y, α, fit_intercept=true, n_iter=2000)

This function uses gradient descent algorithm to find the best weights (θ)
that minimises the mean squared loss between the predictions that the model
generates and the target vector (y).

A tuple of 1D vectors representing the weights (θ)
and a history of loss at each iteration (𝐉) is returned.
"""