My model is based on the dataset 'Gender Recognition by Voice' which consists of 3168 voice samples, half from females and half from males.
The original .wave files have previously been processed in R and are presented as a .csv file with 20 variables, which reflect the frequency parameters of the recorded voices.
The goal of my analysis is to build a model that will predict the gender based on the 20 frequency-related variables (binary classification).
To do so, I compared the performance of a logistic regression model to a random forest algorithm on the same variables.