aastha-ghub / PCA-for-house-price-dataset

Dimension Reduction Techniques (PCA)

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PCA-for-house-price-dataset

Dimension Reduction Techniques (PCA)

Problem Statement:

A key challenge for property sellers is to determine the sale price of the property. The ability to predict the exact property value is beneficial for property investors as well as for buyers to plan their finances according to the price trend. The property prices depend on the number of features like the property area, basement square footage, year built, number of bedrooms, and others. The prices can be predicted more accurately if the number of predictors is less. Several dimension reduction techniques are being applied to decrease this number of predictors.

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Dimension Reduction Techniques (PCA)


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Language:Jupyter Notebook 77.3%Language:Python 22.7%