Decision tree learning - income-based distribution of real estate values

Income has been an essential component of the attractive long-term total returns provided by real estate as an asset class. The annual income returns generated from investing in real estate have been more than 2.5 times higher than stocks and lagged bonds by only 50 basis points. Real estate often provides a steady source of income based on the rent paid by tenants.

Getting ready

In order to perform decision tree classification, we will be using a dataset collected from the real estate dataset.

Step 1 - collecting and describing the data

The dataset titled RealEstate.txt will be used. This dataset is available in TXT format, titled RealEstate.txt. The dataset is in standard format. There are 20,640 rows of data. The 9 numerical variables are as follows:

• MedianHouseValue
• MedianIncome
• MedianHouseAge
• TotalRooms
• TotalBedrooms
• Population
• Households
• Latitude
• Longitude

How to do it...

Let's get into the details.

Step 2 - exploring...