разделить данные на группы областей

#r #split #latitude-longitude #col

#r #разделить #широта-долгота #col

Вопрос:

У меня есть данные о местоположении животных, и я хочу знать домашний диапазон каждой группы точек. Для этого мне нужно разделить данные на группы областей. Местоположения выглядят следующим образом:

Каждая близлежащая точка образует «область поиска» (ARS). И мне нужно разделить группы на фрейме данных. Я думал о разделении данных в соответствии с разницей в широте и долготе. Если местоположения отличаются более чем на 1 градус как по широте, так и по долготе, они будут принадлежать к разным группам (ARS1, ARS2, ARS3 …).

Часть моих данных:

 dput(head(ARS_mcpAA, 100))
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Затем я применю функцию mcp()

1. Это проблема кластеризации, поэтому я предлагаю, чтобы ее лучше задавали при перекрестной проверке . (FWIW, я думаю dbscan , может быть хорошим кандидатом для этого: для этого не требуется знать априори количество кластеров, как это делает KNN. Я попробовал ваши данные, но наличие только 12 точек данных в ваших образцах данных не работает должным образом.)

2. @r2evans Спасибо за ответ. Теперь я обновил свои данные. Можете ли вы помочь с этим кластером?

Ответ №1:

Я подозреваю, что это проблема кластеризации. Одна из проблем, которая является общей для KNN (очень распространенного инструмента кластеризации), заключается в том, что обычно требуется знать априори количество кластеров. Это может быть достигнуто с помощью человека в цикле, но часто вы можете не захотеть полагаться на это.

Еще один хороший инструмент кластеризации dbscan . Я продемонстрирую использование hdbscan :

 library(dbscan)
cl <- hdbscan(dat[,1:2], minPts = 5)
plot(lat ~ lon, data=dat, col = cl$cluster   1, pch = 16)

Возможно, вы предпочтете немного большую группировку

 cl <- hdbscan(dat[,1:2], minPts = 10)
plot(lat ~ lon, data=dat, col = cl$cluster   1, pch = 16)

Это показывает иерархический DBSCAN, его также может быть разумно использовать dbscan .

 cl <- dbscan(dat[,1:2], eps=0.5) # play with eps

1. замечательно! это именно то, что я хочу! Но, как я могу вставить эти группы в фрейм данных. Например: новый столбец с: «group1, group2 ….»? @r2evans

2. dat$grp <- cl$cluster даст вам столбец целых чисел на основе 0. Я бы не стал полагаться на порядок, поэтому 0 он не обязательно будет существенно отличаться от 1 ; поэтому рассматривайте его как категориальное целое число, а не порядковый номер. Кроме того, я считаю, что есть стохастический компонент dbscan , поэтому я не знаю, можете ли вы полагаться на определенную точку, всегда группирующуюся как одно и то же число. (Я не могу запустить его в данный момент, так что я могу ошибаться, но … имейте это в виду, если вы видите различную производительность.)

3. Спасибо! @r2evans