基于多个离散属性的组/簇对象列表
我有一个具有属性的对象列表，例如颜色、长度、宽度以及重要的价格。我最终尝试将列表划分为最大的子集，以便每个子集成员具有相同的价格，并且颜色、长度、宽度的每个排列都存在于子集中。
换句话说，我希望能够划分项目集以发现子集，以便每个集合都可以描述为：
- 所有红色、蓝色或绿色且长 10 或 11 英寸以及高 4 英寸的对象成本为 5 美元
- 所有红色或绿色且 12 英寸长和 4 英寸高的物体均为 6 美元，
- 蓝色 12X4 物体为 6.50 美元
- 等等，
目标是让子集包含尽可能多的项目。
我已经研究这个问题有一段时间了，我认为答案（或近似值）可能来自聚类技术。然而，我一直很难想出一个距离矩阵来提供我正在寻找的结果。有谁知道如何解决这个问题。
更好的解释
给定与上述类似的对象列表，按价格将它们分组为最小数量的完整子集。
I have a list of objects with attributes eg Color, Length, Width and importantly Price. I am ultimately trying to partition the list into the largest subsets so that each subset member has the same price and every permutation of color, length, width is present in the subset.
In other words I want to be able to divide the item set to discover subsets so that each set can be described like:
- all objects that are red, blue, or green and either 10 or 11 inches long as well as 4 inches high cost $5
- All objects that are red or green and 12 inches long and 4 inches high are $6
- A blue 12X4 object is $6.50
- etc. etc.
with the goal of having the subsets contain the most items possible.
I've been wrestling with the problem for a while now, and I think the answer (or a close approximation) might come from clustering techniques. However, I've been hard pressed to come up with a distance matrix that will provide the results I am looking for. Does anyone have any insight into how to solve this problem.
Better Explanation
Given a list of objects similar to the ones above group them into the smallest number of complete subsets by price.
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好吧，第一步是根据价格来划分整个事情。
从那里看来，您想要一个关于其他特征的完整性样本，而不是聚类。如果你想要“每种颜色的排列等等”。以我理解的任何方式，这都不是聚类！听起来像是反聚类！
无论如何，我发现你对最终目标的描述相当令人困惑。
Well, step one is to partition the whole thing on price.
From there it sounds like you want a completeness sample over the other traits, not clustering. If you want "every permutation of color, etc." that isn't clustering, in any ways that I understand! It sounds like anti-clustering!
In any case, I find your description of your end goal quite confusing.