the data set

In this assignment vou are going to predict the prices of 5 new houses (a4 test.csv - the testing dataset) built in Santa Maria-Orcutt. As a training dataset, you are given (a4 train.csv) the sale prices of 30 similar houses in Santa Maria-Orcutt. You are required to build a linear regression model based on the dataset provided to you. Use this linear regression model to predict/estimate the prices for the 5 new houses. You are free to choose as many IVs as possible for a good prediction. Print the coefficients (same as slopes), ? (the intercept), ?'s (the slopes), R2 and the predicted prices as: Coefficient Area Age Bedrooms Beta O= [xxxx] Beta s= [xxxx , predictedPrices[xx , xxxx) XxXx, R-squared-0.83423 To test vour code vour R value should be close to the one listed above To read different columns from a CSV file: dataset-pandas. read csva4 tran.csv) Xs - dataset[[ 'Bedrooms, 'Age', 'Area' ]] In this assignment vou are going to predict the prices of 5 new houses (a4 test.csv - the testing dataset) built in Santa Maria-Orcutt. As a training dataset, you are given (a4 train.csv) the sale prices of 30 similar houses in Santa Maria-Orcutt. You are required to build a linear regression model based on the dataset provided to you. Use this linear regression model to predict/estimate the prices for the 5 new houses. You are free to choose as many IVs as possible for a good prediction. Print the coefficients (same as slopes), ? (the intercept), ?'s (the slopes), R2 and the predicted prices as: Coefficient Area Age Bedrooms Beta O= [xxxx] Beta s= [xxxx , predictedPrices[xx , xxxx) XxXx, R-squared-0.83423 To test vour code vour R value should be close to the one listed above To read different columns from a CSV file: dataset-pandas. read csva4 tran.csv) Xs - dataset[[ 'Bedrooms, 'Age', 'Area' ]]