[英]What kind of model would be suitable when I want to consider several things about an attribute?
I'm struggling to figure out what machine learning/deep learning models would be suitable for what I want to achieve我正在努力弄清楚哪种机器学习/深度学习模型适合我想要实现的目标
I am trying to create a model which will recommend the optimal item purchases which will give me the highest percentage chance of winning a game.我正在尝试创建一个模型,该模型会推荐最佳的物品购买,这将使我赢得比赛的机会最高。 I have enough data (hopefully) to create the model but I want to consider the item purchased and also at what stage in the game was purchased.我有足够的数据(希望如此)来创建模型,但我想考虑购买的物品以及购买游戏的哪个阶段。 Can I just add this in as another variable by itself?我可以将它作为另一个变量单独添加吗?
Imagine there are 3 items: A, B, and C, and 2 different shops at furthering stages in the game.假设有 3 个项目:A、B 和 C,以及 2 个不同的商店处于游戏的进一步阶段。 I want my model to be able to see if the stage of purchase makes a difference for the items.我希望我的模型能够查看购买阶段是否对商品产生影响。 If item A is bought at stage 2 is it still useful at that point in the game, or is it now a weaker choice compared to item B?如果物品 A 在第 2 阶段购买,它在游戏的那个阶段是否仍然有用,或者它现在是一个比物品 B 更弱的选择?
However, in my real-life scenario, there will be way more items, shops, and other limitations.然而,在我的真实场景中,会有更多的物品、商店和其他限制。 I just can't figure out how I can consider items, and stage when some items might be missing entirely from a run of the game.我只是想不通如何考虑物品,以及在游戏运行中可能完全缺少某些物品的阶段。
Originally my plan was to use logistic regression to create my model but now I do not know if it will be able to handle the complexity well enough and if I should attempt to use a deep learning method instead.最初我的计划是使用逻辑回归来创建我的模型,但现在我不知道它是否能够很好地处理复杂性以及我是否应该尝试使用深度学习方法来代替。 I have not attempted to create any model yet as I feel I am not understanding how to apply any techniques to my problem.我还没有尝试创建任何模型,因为我觉得我不了解如何将任何技术应用于我的问题。
Here is my understanding of your question -这是我对你的问题的理解 -
This is a game with a player who, at every stage has an option of purchasing an item from a specific shop.这是一款玩家在每个阶段都可以选择从特定商店购买物品的游戏。 Depending on the item, shop, and the stage at which it was purchased the user will get a certain reward.根据商品、商店和购买阶段,用户将获得一定的奖励。
This could be framed as Reinforcement Learning (RL) problem.这可以被定义为强化学习 (RL) 问题。 I believe DQN will work for the above description.我相信 DQN 将适用于上述描述。 RL has the following components - State, Action, Reward, Next State that you need to set up. RL 具有以下组件 - State、Action、Reward、您需要设置的 Next State。 For your problem, I would design the algorithm in the following way -对于您的问题,我将按以下方式设计算法 -
State - A tuple consisting of (Stage, Amount the player has earned) Action - [Item A1, Item B1, Item C1, Item A2, Item B2, Item C2] Here the player has to choose an action of purchasing an Item A, B or C from shop 1 or 2. Reward - The reward the player gets for taking a specific action at some stage Next State - A tuple consisting of (Stage + 1, Amount the player has earned)状态 - 由(阶段,玩家获得的金额)组成的元组 动作 - [物品 A1,物品 B1,物品 C1,物品 A2,物品 B2,物品 C2] 玩家必须选择购买物品 A 的动作, B 或 C 来自商店 1 或 2。 奖励 - 玩家在某个阶段采取特定行动获得的奖励 下一个状态 - 由(阶段 + 1,玩家获得的金额)组成的元组
RL is quite good at learning the rules of a game and getting the optimal score. RL 非常擅长学习游戏规则并获得最佳分数。
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