AutomobilePricePrediction_IT16170094

This machine learning experiment predicts the price of a car based on different variables such as make and technical specifications. To make numerical predictions, Regression algorithm (Linear Regression) is used. Automobile price data (Raw) is used as the data source. The missing values of the data set are cleaned in preprocessing process, prerior to data analyzation. After defining individual measurable properties (features) as make; body-style, wheel-base, engine-size, horsepower, peak-rpm, highway-mpg and price, the model is trained with linear regression algorithm. The output show the predicted values for price and the known values from the test data.