Predicting the Price of New York City Airbnbs

How can one predict the price of a New York City Airbnb? We are trying to create a machine learning model that can predict the price of a NYC Airbnb given some factors with high accuracy.

How can one predict the price of a New York City Airbnb? We are trying to create a machine learning model that can predict the price of a NYC Airbnb given some factors with high accuracy. There are many factors that contribute to pricing an Airbnb. This model is important because it can help people list their Airbnb for a fair price and help a renter determine if a listing price is fair. We first found a dataset containing the price of New York City Airbnbs and many features about these houses. This dataset also contained many factors about the houses that could be important for predicting prices. We then condensed the data into only the data that we thought were important. We compared several regression models to see which would predict the price best. The random forest regressor predicted the price with about 27% away from the price on average. The SGD regression predicted the price with an error of about 42%. Our model wasn’t very accurate when predicting the price. To accurately predict the price, more factors about the housing are most likely needed. Some of these could be square footage, bathrooms, and bedrooms. Though, these weren’t on the dataset we used.

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