Timeline for How to partition set of items into subsets with similar mean, variance and number of elements - looking for some help
Current License: CC BY-SA 3.0
18 events
| when toggle format | what | by | license | comment | |
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| Jun 11, 2018 at 17:51 | vote | accept | blazej | ||
| Dec 9, 2017 at 9:05 | comment | added | ttnphns |
for a dataframe like this:, and then follows some code, not the data. It is a very bad practice to not show data, only to show uncommented code, R in this instance, - because some people may be not R users.
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| Dec 9, 2017 at 7:43 | answer | added | Fred Viole | timeline score: 1 | |
| Nov 27, 2017 at 20:46 | review | Close votes | |||
| Nov 29, 2017 at 11:31 | |||||
| Nov 25, 2017 at 19:37 | history | edited | blazej | CC BY-SA 3.0 |
rearranged post
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| Nov 25, 2017 at 19:31 | history | edited | blazej | CC BY-SA 3.0 |
rearranged post
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| Nov 25, 2017 at 19:05 | comment | added | Bill | researchgate.net/profile/Jose_Moreno-Torres/publication/… | |
| Nov 25, 2017 at 19:05 | comment | added | Bill | Unfortunately, this is not something I know about. I googled and found that this is a topic which comes up in cross-validation. The paper I link below suggests an algorithm which is 1) choose an element randomly and assign it to set 1. 2) find the closest 5 elements to the one you chose in step 1 and assign these to sets 2 through 6. 3) keep doing this until you run out of elements or your sets are full. You need to operationalize closest in step 2 with some distance measure. | |
| Nov 25, 2017 at 18:48 | history | edited | blazej | CC BY-SA 3.0 |
added 155 characters in body
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| Nov 25, 2017 at 18:45 | comment | added | blazej | Bill I just finished editing my original post with more code and strategies I came up with, would like to take a look at it? Answering your question: I would like to avoid random sampling and go for a strategy finding the best possible (optimal) solution. One important thing to note here: valence, agency and communion ratings are not normally distributed. | |
| Nov 25, 2017 at 18:38 | history | edited | blazej | CC BY-SA 3.0 |
added some more thoughts
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| Nov 25, 2017 at 18:30 | comment | added | Bill | OK, got it. If you just want the theoretical distributions in the sub-samples to be the same, then dividing the sample randomly does that. So, I assume you want the empirical distributions of the variables to be the same in the different sub-samples. Right? Like, you want both the population means and the sample means to be the same, not just the population means. | |
| Nov 25, 2017 at 18:20 | comment | added | blazej | Thanks for stopping by Bill. No that's (probably) not what I want. I'd like to get 6 sets of 20 elements each, where valence, agency and communion have similar mean and variance between and within those 6 sets. In other words I'd like to get set as similar as possible to each other. | |
| Nov 25, 2017 at 18:08 | comment | added | Bill | I don't understand what you want to do. Given the data in your R code, you want to divide up the observations into groups? Like, group 1 would be observations with valence around -1, agency around 1, and communion around 0. Group 2 would be observations with valence around 2, agency around 0, and communion around 0. Etc? Like that or something else? | |
| Nov 25, 2017 at 16:59 | history | edited | blazej | CC BY-SA 3.0 |
added partitioning tag as this might be closer related
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| Nov 24, 2017 at 20:33 | comment | added | blazej | This thing is really bugging me and I would love to offer a bounty if only I could. | |
| Nov 24, 2017 at 17:54 | history | edited | blazej | CC BY-SA 3.0 |
edited title
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| Nov 24, 2017 at 15:03 | history | asked | blazej | CC BY-SA 3.0 |