R machine learning

In this section, we will use an approach for machine learning where we will do the following:

• Partition the dataset into a training and testing set
• Generate a model of the data
• Test the efficiency of our model

 

Dataset

Machine learning works by featuring a dataset that we will break up into a training section and a testing section. We will use the training data to come up with a model. We can then prove or test that model against the testing dataset.

For a dataset to be usable, we need at least a few hundred observations. I am using the housing data from http://uci.edu. Let's load the dataset by using the following command:

housing <- read.table("http://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data") 

The site documents the names of the variables as follows:

Variables	Description
CRIM	Per capita crime rate
ZN	Residential zone rate percentage
INDUS	Proportion of non-retail business in town
CHAS	Proximity to Charles River (Boolean)
NOX	Nitric oxide concentration
RM...