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,这是最右边的列。如您所见,我的数据位于小数点后第6位。
然而,WEKA的预测仅排在第3位。以下是名为“预测”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
正如您所看到的,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而不是更精确的小十进制数。
我在“简单命令行”而不是GUI上使用WEKA。我建立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
([删除路径]:我刚刚删除了隐私的完整路径名)
如您所见,我发现这个“-num-decimal-places”开关用于创建模型。
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,因为在这种情况下WEKA不允许它出于某种原因。 “预测”是我想要的预测文件。
所以我做了这两个命令,并没有改变预测中的小数位数!它仍然只有3个。
我已经在Weka decimal precision看了这个答案pentaho forum和这个答案,但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改变小数位数?但我只是想确定一下。
有没有人知道解决此问题的方法?理想情况下,解决方案将在命令行上,但如果您只知道如何在GUI中执行此操作,那就没问题。
答案 0 :(得分:1)
我只想找到一个解决方法,即简单地将数据缩放/乘以1000,然后得到预测,然后在完成时将其乘以1/1000得到原始比例。有点在盒子外面,但是它有效。
编辑:另一种方法:来自http://weka.8497.n7.nabble.com/Changing-decimal-point-precision-td43393.html的Peter Reutemann回答:
这已经存在了很长时间。 ;-)“ - p”是真的 输出预测的老式方式。使用 “-classifications”选项,您可以指定输出的格式 进入(例如CSV)。使用该选项指定的类必须 来源于 “weka.classifiers.evaluation.output.prediction.AbstractOutput”: http://weka.sourceforge.net/doc.dev/weka/classifiers/evaluation/output/prediction/AbstractOutput.html
以下是使用12位小数作为预测输出的示例 使用Java: https://svn.cms.waikato.ac.nz/svn/weka/trunk/wekaexamples/src/main/java/wekaexamples/classifiers/PredictionDecimals.java