WEKA 更改预测中的小数位数

Question

我正在尝试从 WEKA 获得精确的预测，我需要增加它为预测数据输出的小数位数。

我的 .arff 训练集如下所示：

@relation TrainSet

@attribute TimeDiff1 numeric
@attribute TimeDiff2 numeric
@attribute TimeDiff3 numeric
@attribute TimeDiff4 numeric
@attribute TimeDiff5 numeric
@attribute TimeDiff6 numeric
@attribute TimeDiff7 numeric
@attribute TimeDiff8 numeric
@attribute TimeDiff9 numeric
@attribute TimeDiff10 numeric
@attribute LBN/Distance numeric
@attribute LBNDiff1 numeric
@attribute LBNDiff2 numeric
@attribute LBNDiff3 numeric
@attribute Size numeric
@attribute RW {R,W}
@attribute 'Response Time' numeric

@data

0,0,0,0,0,0,0,0,0,0,203468398592,0,0,0,32768,R,0.006475
0.004254,0,0,0,0,0,0,0,0,0,4564742206976,4361273808384,0,0,65536,R,0.011025
0.002128,0.006382,0,0,0,0,0,0,0,0,4585966117376,21223910400,4382497718784,0,4096,R,0.01389
0.001616,0.003744,0,0,0,0,0,0,0,0,4590576115200,4609997824,25833908224,4387107716608,4096,R,0.005276
0.002515,0.004131,0.010513,0,0,0,0,0,0,0,233456156672,-4357119958528,-4352509960704,-4331286050304,32768,R,0.01009
0.004332,0.006847,0.010591,0,0,0,0,0,0,0,312887472128,79431315456,-4277688643072,-4273078645248,4096,R,0.005081
0.000342,0.004674,0.008805,0,0,0,0,0,0,0,3773914294272,3461026822144,3540458137600,-816661820928,8704,R,0.004252
0.000021,0.000363,0.00721,0,0,0,0,0,0,0,3772221901312,-1692392960,3459334429184,3538765744640,4096,W,0.00017
0.000042,0.000063,0.004737,0.01525,0,0,0,0,0,0,3832104423424,59882522112,58190129152,3519216951296,16384,W,0.000167
0.005648,0.00569,0.006053,0.016644,0,0,0,0,0,0,312887476224,-3519216947200,-3459334425088,-3461026818048,19456,R,0.009504

我正在尝试获取响应时间的预测值，这是最右边的一列。如您所见，我的数据保留到小数点后第六位。

然而，WEKA 的预测只进行到第 3 次。以下是名为 "predictions" 的文件的结果：

    inst#     actual  predicted      error
        1      0.006      0.005     -0.002 
        2      0.011      0.017      0.006 
        3      0.014      0.002     -0.012 
        4      0.005      0.022      0.016 
        5      0.01       0.012      0.002 
        6      0.005      0.012      0.007 
        7      0.004      0.018      0.014 
        8      0          0.001      0     
        9      0          0.001      0     
       10      0.01       0.012      0.003

如您所见，这极大地限制了我预测的准确性。对于小于 0.0005 的非常小的数字（如第 8 行和第 9 行），它们将显示为 0 而不是更准确的小十进制数。

我在 "Simple Command Line" 上使用 WEKA 而不是 GUI。我构建模型的命令如下所示：

java weka.classifiers.trees.REPTree -M 2 -V 0.00001 -N 3 -S 1 -L -1 -I 0.0 -num-decimal-places 6 \
   -t [removed path]/TrainSet.arff \
   -T [removed path]/TestSet.arff \
   -d [removed path]/model1.model > \
   [removed path]/model1output

([已删除路径]：出于隐私考虑，我刚刚删除了完整路径名)

如您所见，我发现了这个用于创建模型的“-num-decimal-places”开关。

然后我使用以下命令进行预测：

java weka.classifiers.trees.REPTree \
    -T [removed path]/LUN0train.arff \
    -l [removed path]/model1.model -p 0 > \
    [removed path]/predictions

我不能在这里使用“-num-decimal places”开关，因为出于某种原因 WEKA 不允许在这种情况下使用它。 "predictions" 是我想要的预测文件。

所以我执行了这两个命令，并没有改变预测中的小数位数！还是只有3.

我已经看过这个答案，Weka decimal precision, and this answer on the pentaho forum，但是没有人提供足够的信息来回答我的问题。这些答案暗示可能无法更改小数位数？但我只是想确定一下。

有人知道解决这个问题的方法吗？理想的解决方案是在命令行上，但如果您只知道如何在 GUI 中执行，那没关系。

Answer 1

我只是想出了一个解决方法，就是简单地 scale/multiply 将数据乘以 1000，然后得到你的预测，然后在完成后将它乘回 1/1000 以获得原始比例。有点开箱即用，但它确实有效。

编辑：另一种方法：来自 http://weka.8497.n7.nabble.com/Changing-decimal-point-precision-td43393.html 的 Peter Reutemann 的回答：

This has been around for a long time. ;-) "-p" is the really old-fashioned way of outputting the predictions. Using the "-classifications" option, you can specify what format the output is to be in (eg CSV). The class that you specify with that option has to be derived from "weka.classifiers.evaluation.output.prediction.AbstractOutput": http://weka.sourceforge.net/doc.dev/weka/classifiers/evaluation/output/prediction/AbstractOutput.html

Here is an example of using 12 decimals for the prediction output using Java: https://svn.cms.waikato.ac.nz/svn/weka/trunk/wekaexamples/src/main/java/wekaexamples/classifiers/PredictionDecimals.java

WEKA 更改预测中的小数位数

WEKA Changing number of decimal places in predictions

precision

machine-learning

command-line-interface

weka

arff