《绝地求生》玩家排名预测
---- 你能预测《绝地求生》玩家战斗结束后的排名吗？
一、项目背景
【项目简介】
绝地求生(Player unknown’s Battlegrounds)，俗称吃鸡，是一款战术竞技型射击类沙盒游戏。
这款游戏是一款大逃杀类型的游戏，每一局游戏将有最多100名玩家参与，他们将被投放在绝地岛(battlegrounds)上，在游戏的开始时所有人都一无所有。玩家需要在岛上收集各种资源，在不断缩小的安全区域内对抗其他玩家，让自己生存到最后。
本作拥有很高的自由度，玩家可以体验飞机跳伞、开越野车、丛林射击、抢夺战利品等玩法，小心四周埋伏的敌人，尽可能成为最后1个存活的人。
该游戏中，玩家需要在游戏地图上收集各种资源，并在不断缩小的安全区域内对抗其他玩家，让自己生存到最后。
【项目涉及知识点】
sk-learn基本操作
数据基本处理
机器学习基本算法的使用
二、数据集介绍
本项目中，将为您提供大量匿名的《绝地求生》游戏统计数据。
其格式为每行包含一个玩家的游戏后统计数据，列为数据的特征值。
数据来自所有类型的比赛：单排，双排，四排；不保证每场比赛有100名人员，每组最多4名成员。
文件说明:
train_V2.csv - 训练集
test_V2.csv - 测试集
数据集局部图如下图所示:
数据集中字段解释：
见【附件一】: 数据集中字段解释
三、项目评估方式
你必须创建一个模型，根据他们的最终统计数据预测玩家的排名，从1（第一名）到0（最后一名）。
最后结果通过平均绝对误差（MAE）进行评估，即通过预测的winPlacePerc和真实的winPlacePerc之间的平均绝对误差
关于MAE:
sklearn.metrics.mean_absolute_error
四、比较结果提交内容
参赛小组最后提交
1.运行结果（以txt文件保存）
2.运行代码（.py或者.pynb）
同时准备10-15 min的结果展示。
【附件一】
数据集中字段解释
- Id [用户id]
- Player’s Id
- groupId [所处小队id]
- ID to identify a group within a match. If the same group of players plays in different matches, they will have a different groupId each time.
- matchId [该场比赛id]
- ID to identify match. There are no matches that are in both the training and testing set.
- assists [助攻数]
- Number of enemy players this player damaged that were killed by teammates.
- boosts [使用能量,道具数量]
- Number of boost items used.
- damageDealt [总伤害]
- Total damage dealt. Note: Self inflicted damage is subtracted.
- DBNOs [击倒敌人数量]
- Number of enemy players knocked.
- headshotKills [爆头数]
- Number of enemy players killed with headshots.
- heals [使用治疗药品数量]
- Number of healing items used.
- killPlace [本场比赛杀敌排行]
- Ranking in match of number of enemy players killed.
- killPoints [Elo杀敌排名]
- Kills-based external ranking of player. (Think of this as an Elo ranking where only kills matter.) If there is a value other than -1 in rankPoints, then any 0 in killPoints should be treated as a “None”.
- kills [杀敌数]
- Number of enemy players killed.
- killStreaks [连续杀敌数]
- Max number of enemy players killed in a short amount of time.
- longestKill [最远杀敌距离]
- Longest distance between player and player killed at time of death. This may be misleading, as downing a player and driving away may lead to a large longestKill stat.
- matchDuration [比赛时长]
- Duration of match in seconds.
- matchType [比赛类型(小组人数)]
- String identifying the game mode that the data comes from. The standard modes are “solo”, “duo”, “squad”, “solo-fpp”, “duo-fpp”, and “squad-fpp”; other modes are from events or custom matches.
- maxPlace [本局最差名次]
- Worst placement we have data for in the match. This may not match with numGroups, as sometimes the data skips over placements.
- numGroups [小组数量]
- Number of groups we have data for in the match.
- rankPoints [Elo排名]
- Elo-like ranking of player. This ranking is inconsistent and is being deprecated in the API’s next version, so use with caution. Value of -1 takes place of “None”.
- revives [救活队员的次数]
- Number of times this player revived teammates.
- rideDistance [驾车距离]
- Total distance traveled in vehicles measured in meters.
- roadKills [驾车杀敌数]
- Number of kills while in a vehicle.
- swimDistance [游泳距离]
- Total distance traveled by swimming measured in meters.
- teamKills [杀死队友的次数]
- Number of times this player killed a teammate.
- vehicleDestroys [毁坏机动车的数量]
- Number of vehicles destroyed.
- walkDistance [步行距离]
- Total distance traveled on foot measured in meters.
- weaponsAcquired [收集武器的数量]
- Number of weapons picked up.
- winPoints [胜率Elo排名]
- Win-based external ranking of player. (Think of this as an Elo ranking where only winning matters.) If there is a value other than -1 in rankPoints, then any 0 in winPoints should be treated as a “None”.
- winPlacePerc [百分比排名]
- The target of prediction. This is a percentile winning placement, where 1 corresponds to 1st place, and 0 corresponds to last place in the match. It is calculated off of maxPlace, not numGroups, so it is possible to have missing chunks in a match.