Automobile Price Prediction Experiment created on 2/15/2020

We used linear regression algorithm to predict the price of automobile cars. Training dataset was 75% of the dataset and 25% of the dataset was testing dataset. Standard deviation of original price value was 8294.6886. Standard deviation of predicted price value was 7323.458. Predict price values are quite similar, but there is considerable deviation between the 2 values. Price of the cars was dependant on the features and specifications of the cars. To reduce this deviation and the inequility of the price colomn values and score value coloumn we need to do some changes in the dataset. I assume that number of selected columns taken was bit more. So we have reduce some of the columns. Besides if we improve the data in the dataset by adding some more rows, we would be able to get accurate results in the scored values.