Here are 10 popular datasets that you can use to perform regression algorithms:
1. Boston Housing Dataset: This dataset contains information about housing prices in Boston. It includes various features such as crime rate, number of rooms, and proximity to employment centers. You can find it [here]
2. California Housing Dataset: This dataset contains housing information for various locations in California. It includes features such as population, median income, and median house value. You can find it [here]
3. Ames Housing Dataset: This dataset contains housing information for the city of Ames, Iowa. It includes features such as the size of the house, number of bedrooms, and neighborhood information. You can find it [here]
4. Wine Quality Dataset: This dataset contains information about the quality of different wines. It includes features such as acidity, pH levels, and alcohol content. You can find it [here]
5. Advertising Dataset: This dataset contains information about advertising budgets and their corresponding sales. It includes features such as TV, radio, and newspaper advertising expenses. You can find it [here]
6. Energy Efficiency Dataset: This dataset contains information about the energy efficiency of buildings. It includes features such as building parameters and heating load. You can find it [here]
7. Bike Sharing Dataset: This dataset contains information about the usage of a bike-sharing system. It includes features such as weather conditions, time of day, and the number of bike rentals. You can find it [here]
8. Concrete Compressive Strength Dataset: This dataset contains information about the compressive strength of different types of concrete. It includes features such as cement, water, and aggregate proportions. You can find it [here]
9. Forest Fires Dataset: This dataset contains information about forest fires in a region of Portugal. It includes features such as temperature, humidity, and wind speed. You can find it [here]
10. Student Performance Dataset: This dataset contains information about student performance in mathematics. It includes features such as study time, family background, and student demographics. You can find it [here]
These datasets provide a good variety of domains and features to explore regression algorithms. Remember to check the specific documentation and data descriptions for each dataset to understand the variable meanings and potential preprocessing steps. Visit our data science courses!
.
