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TensorFlow Decision Forests (TF-DF)

یکی از مدل‌های معروف و کارا در یادگیری ماشین «جنگل تصمیم‌گیری» است. همون‌طور که می‌دونید، این مدل‌ها تفسیرپذیری بالایی دارند و می‌تونند روی دیتای عددی وcategorical بدون پیش‌پردازش کار کنند.
تنسرفلو حالا جنگل تصمیم‌گیری رو به کتابخونه‌ی خودش اضافه کرده تا بتونید این مدل را راحت آموزش بدید، سرو کنید و تفسیر کنید؛ البته این مدل در کتابخونه‌های دیگه مثل sklearn وجود داشتند اما حالا با استفاده از TF-DF می‌توان از ابزارهای دیگه‌ی تنسرفلو مثل TF-serving و TFX به صورت یکپارچه و راحت‌تر استفاده کرد و لذت برد. همچنین تنسرفلو کلی از انواع این مدل رو مثل random forests, gradient-boosted trees, CART, (Lambda)MART, DART, Extra Trees, greedy global growth, oblique trees, one-side-sampling, … اضافه کرده.
نمونه‌ی کد و تفسیر مدل رو در دو عکس بالا آوردیم.

لینک پست توضیح TF-DF:
https://blog.tensorflow.org/2021/05/introducing-tensorflow-decision-forests.html?m=1

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Create: 2021-06-07
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Date: 2025-07-10| NLP stuff

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