twitter的AnomalyDetection 官网效果图如下:
尝试写了下面这个R程序:
get_specify_df <- function(start_ts,stop_ts,category='totaluploadspeed'){
library(httr)
library(rlist)
library(jsonlite) base <- "http://8.8.8.8/serverdata/chartobjects?type=dcache_charge&unit=m&begin_time="
url <- paste(base,start_ts,'&end_time=',stop_ts,sep="")
response <-GET(url)
result <- fromJSON(content(response, as="text",encoding='utf-8'))
if(1 == result$status)
{
# Fix here in the future...
# specify_df <- list.stack(list.select(result$result,result$result$datetime,result$result$category))
specify_df <- list.stack(list.select(result$result,result$result$datetime,result$result$'totaluploadspeed'))
return(specify_df)
}
return(NULL)
} specify_df <- get_specify_df('153386640','1533870000','totaluploadspeed') library(AnomalyDetection)
data(specify_df)
res = AnomalyDetectionTs(specify_df, max_anoms=0.02, direction='both', plot=TRUE)
res$plot
想利用Twitter开源的这个异常检测模块,但是遇到的问题很多,R语言本身可参考资料不多,并且目前貌似已经没人维护了...
所以暂时不想把过多的时间放在这上面,还是改用Python吧...