在以下练习中，您将训练一个二元分类器来区分两种外观相似的稻米品种，并计算相关指标。
您可以使用 Colaboratory 平台直接在浏览器中运行编程练习（无需设置！）。大多数主流浏览器都支持 Colaboratory，并且在桌面版 Chrome 和 Firefox 上进行了最全面的测试。
分类：编程练习
如未另行说明，那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可，并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情，请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
最后更新时间 (UTC)：2024-11-06。
[null,null,["最后更新时间 (UTC)：2024-11-06。"],[[["\u003cp\u003eThis exercise focuses on training a binary classifier to distinguish between two rice species using a provided dataset.\u003c/p\u003e\n"],["\u003cp\u003eThe exercise utilizes Google Colaboratory, allowing direct execution in-browser without requiring any setup on your local machine.\u003c/p\u003e\n"],["\u003cp\u003eGoogle Colaboratory is broadly compatible with major browsers, having undergone extensive testing, specifically on Chrome and Firefox desktop versions.\u003c/p\u003e\n"]]],[],null,["# Classification: Programming exercise\n\nIn the following exercise, you'll train a binary classifier to separate two\nsimilar-looking species of rice and calculate relevant metrics. \n[Open classification exercise](https://colab.research.google.com/github/google/eng-edu/blob/main/ml/cc/exercises/binary_classification_rice.ipynb?utm_source=mlcc&utm_campaign=colab-external&utm_medium=referral&utm_content=binary_classification)\n\nProgramming exercises run directly in your browser (no setup\nrequired!) using the [Colaboratory](https://colab.research.google.com)\nplatform. Colaboratory is supported on most major browsers, and is most\nthoroughly tested on desktop versions of Chrome and Firefox. \n[Help Center](https://support.google.com/machinelearningeducation)"]]