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Prof.Archana lomte


Machine Learning, Linear Regression, House price prediction.


The development of the falling or rising of the house prices has attracted interest from the person in addition as many different interested parties. There square measure many previous researches works that used varied regression techniques to trot out the question of the changes house value. This work considers drawback} of fixing house value as a classification drawback and applies machine learning techniques to predict whether or not or not house prices will rise or fall. This work applies varied feature selection techniques like variance influence issue, info price, principal part analysis and knowledge transformation techniques like outlier and missing value treatment additional as box-cox transformation techniques .The performance of the machine learning techniques is measured by the four parameters of accuracy, precision, specificity and sensitivity. The work considers a pair of distinct value zero and one as varied classes. If the value of the class is zero then we tend to tend to admit that the value of the house has pale and if the value of the class is one then we tend to tend to admit that the value of the house has raised.

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Published in: Volume : 7, Issue : 7
Publication Date: 7/1/2021

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