在ELKI上运行OPTICS算法 [英] Running OPTICS algorithm on ELKI

问题描述

我通常是R用户(刚开始的R用户，但是我开始感到困惑).但是，我听说过有关ELKI的正面信息-特别是它的速度.我碰到了这个旧帖子如何进行分组存储在SQL中的附近的经纬度位置" ，Anony-Mousse发布的答案与我想要执行的操作类似.我希望能够将他完成的每个步骤复制到他在Google云端硬盘上共享的KML文件.

I'm normally an R user (a beginning R user, but I'm starting to get the hang of it). However, I have heard positive things about ELKI--in particular, its speed. I came across this old post "How to group nearby latitude and longitude locations stored in SQL" and the answer posted by Anony-Mousse is similar to what I'd like to do. I would like to be able to replicate each step he has done up to the KML file he has shared on Google Drive.

我已经下载了ELKI并能够运行如下所示的mini-GUI:

I've downloaded ELKI and am able to run the mini-GUI, which looks like the following:

有人可以发布一些步骤来做Anony-Mousse能够做的事情吗?

Could someone post some steps on how to do what Anony-Mousse was able to do?

我的数据本质上非常相似.我在csv文件中有地址解析的地址(更具体地说，每个元组是一个事件，变量/功能/列之一是事件的地理编码的地址)，我想在上面的链接中找到类似于OP的群集

My data is very similar in nature. I have geocoded addresses in a csv file (more specifically, each tuple is an event and one of the variables/features/columns is the geocoded address of the event) and I'm looking to find clusters much like the OP in the link above.

希望Anony-Mousse阅读这篇文章，并进行救援.但是，如果有人可以帮助我，我将不胜感激.

Hopefully, Anony-Mousse will read this post and come to the rescue. But, I'd be grateful if anyone else could help get me on my way.

推荐答案

很抱歉没有跟进.

我没有保存您引用的实验代码.因此，我不记得是否使用python脚本将输出重写为KML(我相信是这样做的)，或者我是否只是从ELKI源复制并粘贴到自定义ResultHandler来生成文件. 可能是第一种，因为用Java编写XML比用Python打印文档要复杂一些(尽管那时也很可能是正确的XML).如果是这样，我可能使用了scipy.spatial包来计算凸包，读取ELKI文本输出相当简单(只需跳过注释行，并将另一个的两个数字列作为坐标)

I did not keep the code for my experiments you refer to. So I don't remember whether I used a python script to rewrite the output to KML (I believe I did so), or whether I just copy&pasted from the ELKI source to a custom ResultHandler to generate the file. Probably the first, because writing XML in Java is a bit more complicated (although also more likely to be correct XML then) than just printing the document in Python. If so, I probably used the scipy.spatial package for computing the convex hull, reading the ELKI text output is fairly trivial (just skip comment lines, and take the two numeric columns of the other as coordinates)

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