Home Price Prediction
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Brian Ruiz
CoPIs:
Mostafa Moamen, Juan Patino
College:
The Dorothy and George Hennings College of Science, Mathematics, and Technology
Major:
Computer Science
Faculty Research Advisor(s):
Ching-yu Huang
Abstract:
This study looks at how different features of a house, like its size, age, number of rooms,
bathrooms, and other features, affect its price. We use 3 datasets with different attributes on a bunch of
homes that include all these details. This helps us see the bigger picture of what makes some homes
more expensive than others. Our main goal is to figure out what matters most when it comes to the
price of a house. We're using simple tools to analyze the data and try to predict home prices based on
the features we mentioned. With 3 different datasets with different attributes, we are researching the
different combinations of features that make the prediction the most accurate. This research is
important because it can help people who are looking to buy a house understand what makes a home
valuable. It can also help those who sell houses or are involved in planning and building homes. We hope
our findings will make it easier for everyone to make smart decisions when it comes to buying, selling, or
building homes.