SharpLearning | Machine learning for C # .Net | Machine Learning library
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QUESTION
I have a machine learning problem where I have obtained very good results on training/test data using both LightGBM
and XGBoost
. The next step is to obtain predictions from one of these models into an existing C# application (.NET Framework 4.6.1) Is there any library that can help me do this? What I have tried so far:
- ML.NET: Should work for
LigthGBM
, but due to this bug it works only for .NET Core. - Windows.ML: This should be able to predict an ONNX model, and I managed to create an ONNX model from my
XGBoost
model. But Windows.ML seems to work only for UWP apps, at least all samples are UWP. - SharpLearning: This library has an interface to
XGBoost
. Unfortunately, it does not support sample weights, which I rely upon. - CNTK: Tried to load the ONNX file (similar to this example), but get: Error: ONNX (TreeEnsembleClassifier) is not supported in CNTK.
Any suggestions, or do I have to wait for ML.NET to fix the bug?
ANSWER
Answered 2019-Jul-11 at 23:29I was able to use LightGBM in a net461
console application. The above bug only occurs if you are using packages.config
to manage your NuGet packages. In order to work around the listed bug in the LightGBM nuget package, you can take one of the following approaches:
- Use a new "SDK-style" .csproj, but set the TargetFramework to
net461
.
Exe
net461
win-x64
Always
- Change your normal .NET Framework .csproj to use
instead of
packages.config
. You can do this in the Package Manager Settings under Tools -> NuGet Package Manager menu. "Default package management format". You can refer to the Migrate from packages.config to PackageReference document for more info.
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