Mallet可以在Linux下工作，但不能在Windows下工作

好的，我正在尝试使用Mallet对Windows中的一些文档进行分类

我是在Linux上实现的。只是无法让它在Windows（目标环境）中执行任务

我已将数据导入.mallet文件

然后使用这些输入数据创建一个分类器

-rw-r--r-- 1 henry henry 15197116 Feb 23 15:56 nntp.classifier

及

但是，当我在Linux中运行时：

bin/mallet分类目录——输入。/testfolder——输出——分类器 分类器

它迭代testfolder中的任何文件，并转储它认为每个文件都是什么类

但如果我在Windows中运行相同的命令：

bin\mallet classify-dir --input ./testfolder --output - --classifier nntp.classifier

它只是转储命令列表：

Mallet 2.0 commands:
  import-dir        load the contents of a directory into mallet instances (one per file)
  import-file       load a single file into mallet instances (one per line)
  import-svmlight   load a single SVMLight format data file into mallet instances (one per line)
  train-classifier  train a classifier from Mallet data files
  train-topics      train a topic model from Mallet data files
  infer-topics      use a trained topic model to infer topics for new documents
  estimate-topics   estimate the probability of new documents given a trained model
  hlda              train a topic model using Hierarchical LDA
  prune             remove features based on frequency or information gain
  split             divide data into testing, training, and validation portions
Include --help with any option for more information

我确实注意到了一件事：我

如果我在linux中运行

bin/mallet-classify-dir--help

，我会得到帮助文件，即每个命令的描述，但是在Windows

bin\mallet-classify-dir--help中的相同内容不会产生相同的结果-只是上面的命令列表。。。（如果输入junk作为命令，则执行相同的操作）

而前面的一个命令，例如
bin/mallet import dir--help
和
bin\mallet import dir--help
生成相同的完整帮助文件输出。
bin目录中的mallet.bat文件有问题。
您应该在以下位置对其进行修改：

@echo off

rem This batch file serves as a wrapper for several
rem  MALLET command line tools.

if not "%MALLET_HOME%" == "" goto gotMalletHome

echo MALLET requires an environment variable MALLET_HOME.
goto :eof

:gotMalletHome

set MALLET_CLASSPATH=%MALLET_HOME%\class;%MALLET_HOME%\lib\mallet-deps.jar
set MALLET_MEMORY=1G
set MALLET_ENCODING=UTF-8

set CMD=%1
shift

set CLASS=
if "%CMD%"=="import-dir" set CLASS=cc.mallet.classify.tui.Text2Vectors
if "%CMD%"=="import-file" set CLASS=cc.mallet.classify.tui.Csv2Vectors
if "%CMD%"=="import-smvlight" set CLASS=cc.mallet.classify.tui.SvmLight2Vectors
if "%CMD%"=="train-classifier" set CLASS=cc.mallet.classify.tui.Vectors2Classify
if "%CMD%"=="classify-dir" set CLASS=cc.mallet.classify.tui.Text2Classify
if "%CMD%"=="classify-file" set CLASS=cc.mallet.classify.tui.Csv2Classify
if "%CMD%"=="train-topics" set CLASS=cc.mallet.topics.tui.Vectors2Topics
if "%CMD%"=="infer-topics" set CLASS=cc.mallet.topics.tui.InferTopics
if "%CMD%"=="estimate-topics" set CLASS=cc.mallet.topics.tui.EvaluateTopics
if "%CMD%"=="hlda" set CLASS=cc.mallet.topics.tui.HierarchicalLDATUI
if "%CMD%"=="prune" set CLASS=cc.mallet.classify.tui.Vectors2Vectors
if "%CMD%"=="split" set CLASS=cc.mallet.classify.tui.Vectors2Vectors
if "%CMD%"=="bulk-load" set CLASS=cc.mallet.util.BulkLoader
if "%CMD%"=="run" set CLASS=%1 & shift

if not "%CLASS%" == "" goto gotClass

echo Mallet 2.0 commands:
echo   import-dir        load the contents of a directory into mallet instances (one per file)
echo   import-file       load a single file into mallet instances (one per line)
echo   import-svmlight   load a single SVMLight format data file into mallet instances (one per line)
echo   train-classifier  train a classifier from Mallet data files
echo   classify-dir      classify the contents of a directory with a saved classifier
echo   classify-file     classify a file with a saved classifier
echo   train-topics      train a topic model from Mallet data files
echo   infer-topics      use a trained topic model to infer topics for new documents
echo   estimate-topics   estimate the probability of new documents given a trained model
echo   hlda              train a topic model using Hierarchical LDA
echo   prune             remove features based on frequency or information gain
echo   split             divide data into testing, training, and validation portions
echo Include --help with any option for more information


goto :eof

:gotClass

set MALLET_ARGS=

:getArg

if "%1"=="" goto run
set MALLET_ARGS=%MALLET_ARGS% %1
shift
goto getArg

:run

java -Xmx%MALLET_MEMORY% -ea -Dfile.encoding=%MALLET_ENCODING% -classpath %MALLET_CLASSPATH% %CLASS% %MALLET_ARGS%

:eof

用于在Windows环境中进行分类

我希望这能有所帮助

Ignazio
请注意，Ignazio提供的.bat文件第23行有一个打字错误（不幸的是，该文件包含在mallet-2.0.7下载中），导致它查找“import smvlight”而不是“import svmlight”，这是帮助信息中指定的。如果要使用此功能，请确保切换“m”和“v”。
。效果很好。你报名来告诉我这件事！我已经安装了Cygwin，并编制了一个完整的列表，其中包括Ant、Bant、Chant和Rant等名称。这将使下一个Windows guy tho.的工作更加轻松。/bin中的其他脚本仍然只是linux。
@echo off

rem This batch file serves as a wrapper for several
rem  MALLET command line tools.

if not "%MALLET_HOME%" == "" goto gotMalletHome

echo MALLET requires an environment variable MALLET_HOME.
goto :eof

:gotMalletHome

set MALLET_CLASSPATH=%MALLET_HOME%\class;%MALLET_HOME%\lib\mallet-deps.jar
set MALLET_MEMORY=1G
set MALLET_ENCODING=UTF-8

set CMD=%1
shift

set CLASS=
if "%CMD%"=="import-dir" set CLASS=cc.mallet.classify.tui.Text2Vectors
if "%CMD%"=="import-file" set CLASS=cc.mallet.classify.tui.Csv2Vectors
if "%CMD%"=="import-smvlight" set CLASS=cc.mallet.classify.tui.SvmLight2Vectors
if "%CMD%"=="train-classifier" set CLASS=cc.mallet.classify.tui.Vectors2Classify
if "%CMD%"=="classify-dir" set CLASS=cc.mallet.classify.tui.Text2Classify
if "%CMD%"=="classify-file" set CLASS=cc.mallet.classify.tui.Csv2Classify
if "%CMD%"=="train-topics" set CLASS=cc.mallet.topics.tui.Vectors2Topics
if "%CMD%"=="infer-topics" set CLASS=cc.mallet.topics.tui.InferTopics
if "%CMD%"=="estimate-topics" set CLASS=cc.mallet.topics.tui.EvaluateTopics
if "%CMD%"=="hlda" set CLASS=cc.mallet.topics.tui.HierarchicalLDATUI
if "%CMD%"=="prune" set CLASS=cc.mallet.classify.tui.Vectors2Vectors
if "%CMD%"=="split" set CLASS=cc.mallet.classify.tui.Vectors2Vectors
if "%CMD%"=="bulk-load" set CLASS=cc.mallet.util.BulkLoader
if "%CMD%"=="run" set CLASS=%1 & shift

if not "%CLASS%" == "" goto gotClass

echo Mallet 2.0 commands:
echo   import-dir        load the contents of a directory into mallet instances (one per file)
echo   import-file       load a single file into mallet instances (one per line)
echo   import-svmlight   load a single SVMLight format data file into mallet instances (one per line)
echo   train-classifier  train a classifier from Mallet data files
echo   classify-dir      classify the contents of a directory with a saved classifier
echo   classify-file     classify a file with a saved classifier
echo   train-topics      train a topic model from Mallet data files
echo   infer-topics      use a trained topic model to infer topics for new documents
echo   estimate-topics   estimate the probability of new documents given a trained model
echo   hlda              train a topic model using Hierarchical LDA
echo   prune             remove features based on frequency or information gain
echo   split             divide data into testing, training, and validation portions
echo Include --help with any option for more information


goto :eof

:gotClass

set MALLET_ARGS=

:getArg

if "%1"=="" goto run
set MALLET_ARGS=%MALLET_ARGS% %1
shift
goto getArg

:run

java -Xmx%MALLET_MEMORY% -ea -Dfile.encoding=%MALLET_ENCODING% -classpath %MALLET_CLASSPATH% %CLASS% %MALLET_ARGS%

:eof