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r - 使用 tidytext 和 broom 但没有找到 LDA_VEM 的 tidier

转载 作者:行者123 更新时间:2023-12-02 06:28:23 26 4
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tidytext 书有主题模型的 tidier 示例:

library(tidyverse)
library(tidytext)
library(topicmodels)
library(broom)

year_word_counts <- tibble(year = c("2007", "2008", "2009"),
+ word = c("dog", "cat", "chicken"),
+ n = c(1753L, 1157L, 1057L))

animal_dtm <- cast_dtm(data = year_word_counts, document = year, term = word, value = n)

animal_lda <- LDA(animal_dtm, k = 5, control = list( seed = 1234))

animal_lda <- tidy(animal_lda, matrix = "beta")

# Console output
Error in as.data.frame.default(x) :
cannot coerce class "structure("LDA_VEM", package = "topicmodels")" to a data.frame
In addition: Warning message:
In tidy.default(animal_lda, matrix = "beta") :
No method for tidying an S3 object of class LDA_VEM , using as.data.frame

复制同样出现的错误 here但在这种情况下 library(tidytext) 是 目前。

下面是所有包的列表及其对应的版本:

 packageVersion("tidyverse")
‘1.2.1’

packageVersion("tidytext")
‘0.1.6’

packageVersion("topicmodels")
‘0.2.7’

packageVersion("broom")
‘0.4.3’

函数调用 sessionInfo() 的输出:

R version 3.4.3 (2017-11-30)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] broom_0.4.3 tidytext_0.1.6 forcats_0.2.0 stringr_1.2.0 dplyr_0.7.4 purrr_0.2.4 readr_1.1.1 tidyr_0.8.0
[9] tibble_1.4.2 ggplot2_2.2.1 tidyverse_1.2.1 topicmodels_0.2-7

loaded via a namespace (and not attached):
[1] modeltools_0.2-21 slam_0.1-42 NLP_0.1-11 reshape2_1.4.3 haven_1.1.1 lattice_0.20-35 colorspace_1.3-2 SnowballC_0.5.1
[9] stats4_3.4.3 yaml_2.1.16 rlang_0.1.6 pillar_1.1.0 foreign_0.8-69 glue_1.2.0 modelr_0.1.1 readxl_1.0.0
[17] bindrcpp_0.2 bindr_0.1 plyr_1.8.4 munsell_0.4.3 gtable_0.2.0 cellranger_1.1.0 rvest_0.3.2 psych_1.7.8
[25] tm_0.7-3 parallel_3.4.3 tokenizers_0.1.4 Rcpp_0.12.15 scales_0.5.0 jsonlite_1.5 mnormt_1.5-5 hms_0.4.1
[33] stringi_1.1.6 grid_3.4.3 cli_1.0.0 tools_3.4.3 magrittr_1.5 lazyeval_0.2.1 janeaustenr_0.1.5 crayon_1.3.4
[41] pkgconfig_2.0.1 Matrix_1.2-12 xml2_1.2.0 lubridate_1.7.2 assertthat_0.2.0 httr_1.3.1 rstudioapi_0.7 R6_2.2.2
[49] nlme_3.1-131 compiler_3.4.3

最佳答案

删除 .Rhistory 和 .RData 导致正确的行为。

关于r - 使用 tidytext 和 broom 但没有找到 LDA_VEM 的 tidier,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/48765936/

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