ML.Net重新训练现有模型，而不是训练新模型 [英] ML.Net retrain existing model rather than training new model

问题描述

我正在训练ML.Net机器学习模型。我可以训练它并从中进行预测，然后从磁盘保存/加载它。但是我需要能够将其从磁盘上加载，然后对其进行重新培训，或者添加新的信息以随着时间的推移对其进行改进。

I am training a ML.Net machine learning model. I can train it and predict from it, and save/load it from the disk. But I need to be able to load it off the disk, then retrain it, or add to it with new information to improve it over time.

有人知道吗有可能吗我没有在MS文档中找到如何做的任何事情，但这对于ML来说是很标准的事情，因此如果无法实现，我会感到惊讶。

Does anyone know if this is possible? I have not found anything in the MS docs of how to do it, but it's a pretty standard thing for ML, so I'd be surprised if it's not possible.

谢谢

推荐答案

此功能存在于ML.NET中，但现有的 LearningPipeline无法实现 API。这将在新的ML.NET API中公开，并且可以找到启用此方案的示例此处。相关代码为：

This functionality exists in ML.NET but it is not possible with the existing LearningPipeline APIs. This will be exposed in the new ML.NET APIs and a sample enabling this scenario can be found here. The relevant code is:

// Train the first predictor.
var trainer = new LinearClassificationTrainer(env, new LinearClassificationTrainer.Arguments
{
    NumThreads = 1
}, "Features", "Label");
var firstModel = trainer.Fit(trainData);

// Train the second predictor on the same data.
var secondTrainer = new AveragedPerceptronTrainer(env, new AveragedPerceptronTrainer.Arguments());

var trainRoles = new RoleMappedData(trainData, label: "Label", feature: "Features");
var finalModel = secondTrainer.Train(new TrainContext(trainRoles, initialPredictor: firstModel.Model));

这些API仍在不断发展，但这也许有所帮助。这还不是官方ML.NET版本的一部分，因此您需要从此处或构建存储库。

These APIs are still in flux, but perhaps this helps. This is not yet part of an official ML.NET release so you would need to get a NuGet from here or build the repo.

注意：我是ML.NET团队的成员。

Note: I am on the ML.NET team.

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