问题描述
我正在遵循用于ML.Net的虹膜教程,我键入了说明,而不是复制/粘贴说明,这样我可以更好地学习API,但是现在遇到了一些错误.
I am following the Iris tutorial for ML.Net, I typed out the instructions instead of copy/pasting them so I could learn the API better, but now I am getting some errors.
当我从教程中运行此行时,会抛出System.Reflection.TargetInvocationException
:
When I run this line from the tutorial a System.Reflection.TargetInvocationException
is thrown:
var model = pipeline.Train<IrisData, IrisPrediction>();
我在运行时遇到的控制台错误是:
The console errors I am getting during runtime are:
Bad value at line 2 in column Label
...
Bad value at line 8 in column Label
Suppressing further bad value messages
...
Processed 150 rows with 150 bad values and 0 format errors
Warning: Term map for output column 'Label' contains no entries.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Using 2 threads to train.
Automatically choosing a check frequency of 2.
Bad value at line 1 in column Label
...
Suppressing further bad value messages
Processed 150 rows with 150 bad values and 0 format errors
Warning: Skipped 150 instances with missing features/label during training
这是我的IrisData
课:
namespace Ronald.A.Fisher
{
public class IrisData
{
[Column("0")]
public float SepalLength;
[Column("1")]
public float SepalWidth;
[Column("2")]
public float PetalLength;
[Column("3")]
public float PetalWidth;
[Column("4")]
[ColumnName("Label")]
public float Label;
}
推荐答案
看了一会儿之后,我意识到我的一列数据类型不正确.
After looking at it for a short while I realized that one of my columns had the incorrect data type.
在用于加载学习数据的类IrisData
中,我为Label
使用了错误的数据类型.因此,控制台消息:Bad value at line 1 in column Label
.
In the class used to load the learning data, IrisData
, I used the incorrect data type for Label
. Hence the console message: Bad value at line 1 in column Label
.
要解决此问题,我将Label
字段的数据类型从float
更改为string
:
To fix this, I changed the data type for the Label
field from float
to string
:
public class IrisData
{
...
[ColumnName("Label")]
public string Label;
}
这篇关于ML.net-列标签中第1行的值不正确的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!