KayleeDavisGitHub / Machine-Learning-R

Replication and notes on machine learning practice in R.

Machine-Learning

-- Replication and notes on machine learning practice --

These files follow an intensive quantiative methods course at The Ohio State University.

Simulation and Bootstrapping

The simulation and bootstrapping R files can be used to generate synthetic data and practice bootstrapping observations.

Penalized Regression Modelling

In these Lab 3 notes I generate data and run various penalized regression models using the carat package. These include the LASSO, ridge, and elastic net models.

Classification, SVMs, Regression Trees

Here the Lab 4 files go over generating synthetic data and using penalized regression models for classification. Lab 4 ends with cleaning text data, and various ways to go about this.

Lab 5 goes into using Support Vector Models (SVMs) and classification trees for classification. Lab 5 uses synthetic data.

Both labs provide vizualizations and attempts to summarize a dense methodological approach by providing .pdf's (and LaTeX code) detailing the intution behind these approaches.

Questions? Email: [e-mail]