Machine learning datasets play a crucial role in the development of algorithms and models. The housing dataset is one of the most popular datasets used for machine learning tasks, especially in the field of predictive analytics.
Overview
The housing dataset contains information about housing in various neighborhoods in a city. It includes attributes such as the number of rooms, age of the house, price, and more. This dataset is often used to predict housing prices based on various features.
Features
Here are some of the key features in the housing dataset:
- Number of Rooms: The number of rooms in the house.
- Age: The age of the house in years.
- Price: The price of the house in thousands of dollars.
- Crime Rate: The crime rate in the neighborhood.
- Area: The size of the house in square feet.
Example
Here's an example of a row from the dataset:
8, 45, 230, 0.5, 1000
This row represents a house with 8 rooms, built 45 years ago, priced at $230,000, a crime rate of 0.5, and an area of 1000 square feet.
Resources
For more information on machine learning datasets, you can visit the following resources: