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Project utilizing linear regression, RF, and SVM to predict housing sale price based on 79 available feature variables.

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Housing Market Analysis

Project utilizing linear regression, RF, and SVM to predict housing sale prices based on 79 available feature variables.

Data Source

Ames Housing Dataset

The dataset used in this project originally comes from the Ames Housing dataset, which was compiled by Dean De Cock for use in data science education (De Cock, 2011). It examines the features of houses sold in Ames, Iowa from 2006-2010.

Aims

  • Identify which housing features are most important for predicting home prices
  • Identify ML model that yields highest accuracy

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Project utilizing linear regression, RF, and SVM to predict housing sale price based on 79 available feature variables.

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