在以下練習中，您將訓練二元分類器，以便區分兩種外觀相似的米，並計算相關指標。
您可以使用 Colaboratory 平台，直接在瀏覽器中執行程式設計練習 (無須進行設定)。Colaboratory 支援大多數主流瀏覽器，且在 Chrome 和 Firefox 電腦版上經過最徹底的測試。
分類：程式設計練習
除非另有註明，否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權，程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
上次更新時間：2024-11-06 (世界標準時間)。
[null,null,["上次更新時間：2024-11-06 (世界標準時間)。"],[[["\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)"]]