Salary-Prediction-with-Machine-Learning

Explanation

The main goal of this project is to build a machine learning model that accurately predicts the salaries of baseball players.

About Dataset

A data frame with 322 observations of major league players on the following 20 variables:

• AtBat: Number of times at bat in 1986

• Hits: Number of hits in 1986

• HmRun: Number of home runs in 1986

• Runs: Number of runs in 1986

• RBI: Number of runs batted in in 1986

• Walks: Number of walks in 1986

• Years: Number of years in the major leagues

• CAtBat: Number of times at bat during his career

• CHits: Number of hits during his career

• CHmRun: Number of home runs during his career

• CRuns: Number of runs during his career

• CRBI: Number of runs batted in during his career

• CWalks: Number of walks during his career

• League: A factor with levels A and N indicating player's league at the end of 1986

• Division: A factor with levels E and W indicating player's division at the end of 1986

• PutOuts: Number of put outs in 1986

• Assists: Number of assists in 1986

• Errors: Number of errors in 1986

• Salary: 1987 annual salary on opening day in thousands of dollars

• NewLeague: A factor with levels A and N indicating player's league at the beginning of 1987