Open amandazhang opened 7 years ago
Feature Selection model with take in 2 d dimensional vectors, representing the two teams playing in the tournament. Each d dimensional vector will contain information about the team for that year. Below are the features we end up using. Regular Season Wins Points per game season average Number of 3's per game Turnovers per game average Assists per game average Conference Championship - binary label Rebounds per game average Steals per game average Whether the team is home or away or neutral (labels -1, 0, and 1)
Western Conference: Golden State vs Portland, LAC vs Utah, SA vs MEM, Hou vs OKC
Eastern Conference: BOS vs CHI, WAS vs ATU, CLE vs IND, TOR vs MIL
Update on playoff game played till 4/19
After first meeting today, we decided to using machine learning tools to build a prediction model for 2016-2017 NBA Playoffs.
TO do list: