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CoreML中的二进制分类模型训练

[英]Binary Classification Model training in CoreML

I have just started exploring CoreML and was wondering if there is a way to train a Binary Classification Model using the same. 我刚刚开始研究CoreML,并且想知道是否有一种方法可以使用它来训练二进制分类模型。

Please provide me any references or examples as I am a ML noob. 请提供任何参考或示例,因为我是ML新手。

Core ML doesn't offer any APIs for building or training models. Core ML不提供任何用于构建或训练模型的API。 It works with models you've already trained elsewhere (Keras, Caffe, etc) to perform whatever prediction or classification task you built the model for. 它可以与您已经在其他地方(Keras,Caffe等)训练过的模型一起使用,以执行为模型构建的任何预测或分类任务。 See Apple's Core ML docs for info on how to convert a model for use with Core ML. 有关如何转换模型以与Core ML一起使用的信息,请参阅Apple的Core ML文档

Core ML offers building and training models as of macOS 10.14 (Mojave). Core ML从macOS 10.14(Mojave)开始提供构建和训练模型。 In XCode you can train models in various ways. 在XCode中,您可以通过各种方式训练模型。

I don't believe they currently support a binary classifier, but if you can build an image set of X and NOT X you could emulate such. 我不认为它们当前支持二进制分类器,但是如果您可以构建X而不是X的图像集,则可以模拟这样的图像。

Apple's Docs: https://developer.apple.com/documentation/create_ml/creating_an_image_classifier_model 苹果文档: https//developer.apple.com/documentation/create_ml/creating_an_image_classifier_model

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