Automobile Price Prediction - IT17030304
How to use Regression algorithms to make numerical predictions.
**Prepare the data**
Clean the data
-Removed normalized-losses column since that column has a large proportion of missing values.
-Removed rows that has missing data
**Define features**
Features
-make, body-style, wheel-base, engine-size, horsepower, peak-rpm, highway-mpg, price
**Choose and apply an algorithm**
Split Data
-75 percent of the data to train the model and hold back 25 percent for testing.
Machine Learning category
-Used Linear Regression module under the Regression category
**Predict new automobile prices**
Run the experiment and view the output from the Score Model