tag:blogger.com,1999:blog-16607461.post8217670245690993518..comments2024-03-29T10:21:47.284+08:00Comments on 布丁布丁吃什麼?: 整合PostgreSQL資料庫的R中文文本探勘 / Chinese Text Mining with R and PostgreSQL布丁布丁吃布丁http://www.blogger.com/profile/13614721642960940190noreply@blogger.comBlogger4125tag:blogger.com,1999:blog-16607461.post-15860329922818890482016-11-13T10:25:15.278+08:002016-11-13T10:25:15.278+08:00To St W,
不客氣,祝你能夠順利進行文本探勘!To St W,<br /><br />不客氣,祝你能夠順利進行文本探勘!布丁布丁吃布丁https://www.blogger.com/profile/18000418899714977849noreply@blogger.comtag:blogger.com,1999:blog-16607461.post-75035282046951534912016-11-09T09:06:44.652+08:002016-11-09T09:06:44.652+08:00好的,
我再試看看,
感謝您熱心回覆!好的,<br />我再試看看,<br />感謝您熱心回覆!Anonymoushttps://www.blogger.com/profile/05374273285025980723noreply@blogger.comtag:blogger.com,1999:blog-16607461.post-13331143691885937122016-11-08T23:06:56.816+08:002016-11-08T23:06:56.816+08:00To St W,
這是因為新版R的問題。新版的R連帶影響到新版的tm跟segmentCN套件,全部...To St W,<br /><br />這是因為新版R的問題。新版的R連帶影響到新版的tm跟segmentCN套件,全部都不能用這篇文章的R Script。<br />可以看我在另一篇最後的討論:<br />http://blog.pulipuli.info/2016/11/r-draw-word-cloud-in-r.html#postcatar-draw-word-cloud-in-r.html0_anchor5<br /><br />這篇文章的R是用3.0.2版,請試著去找這一版的R來安裝,然後再努力克服套件安裝的問題。<br />這裡下載Windows的R 3.0.2版,https://mirrors.tuna.tsinghua.edu.cn/CRAN/bin/windows/base/old/3.0.2/<br />但是Windows的R會有中文亂碼的問題,無法完全克服,我建議改用Linux<br />舊版套件安裝的問題請看這一篇:http://blog.pulipuli.info/2016/11/rubuntur-how-to-install-archived.html<br /><br />你也可以架設虛擬機器RStudio Server來做這件事情,我保證絕對可以正常運作<br />http://blog.pulipuli.info/2016/11/rrstudio-server-openvz-standalone-r.html<br /><br />布丁布丁吃布丁https://www.blogger.com/profile/18000418899714977849noreply@blogger.comtag:blogger.com,1999:blog-16607461.post-50926732712208323872016-11-08T22:34:02.743+08:002016-11-08T22:34:02.743+08:00您好:
拜讀執行後,會產生錯誤訊息如下,煩請撥冗賜教,謝謝!
Error in FUN(X[[i]...您好:<br />拜讀執行後,會產生錯誤訊息如下,煩請撥冗賜教,謝謝!<br /> Error in FUN(X[[i]], ...) : Please input character! <br />Show Traceback 呈現:<br />6.<br />stop("Please input character!") <br />5.<br />FUN(X[[i]], ...) <br />4.<br />lapply(X, FUN, ...) <br />3.<br />mclapply(content(x), FUN, ...) <br />2.<br />tm_map.VCorpus(R_corpus, segmentCN, nature = TRUE) <br />1.<br />tm_map(R_corpus, segmentCN, nature = TRUE) Anonymoushttps://www.blogger.com/profile/05374273285025980723noreply@blogger.com