Data Impurity and EntropyYouTube↗  IA↗(long shot)
Education  21.3K views 27 likes 48 dislikes   23 Feb 2015
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Now were going to talk about something that's very important for
والآن سنتحدث عن أمر بالغ الأهمية بالنسبة إلى
decision trees, and that is entropy.
أشجار القرار، ألا وهو الإنتروبي.
Entropy is basically the thing that controls how a decision tree
الإنتروبي في الأساس هو ما يتحكم في طريقة
decides where to split the data.
تحديد شجرة القرار لموضع فصل البيانات
So, entropy is this very powerful thing.
وبالتالي يعد الإنتروبي أمرًا قوي التأثير للغاية.
What's the definition?
فما هو تعريفه؟
It's a measure of impurity in a bunch of examples.
هو قياس للعيوب الموجودة في مجموعة من الأمثلة.
Let me show you what I mean.
دعوني أوضح لكم ما أعنيه.
Sebastian self-driving car data, we have the grade and
في بيانات Sebastian الخاصة بالسيارة ذاتية القيادة، لدينا درجة التضاريس
the bumpiness of the terrain, like we did before.
ووعورتها، كما فعلنا من قبل.
But, let's suppose that there's a new variable, a new feature now
ولكن لنفترض أن هناك متغيرًا جديدًا، أو ميزة جديدة الآن
that we're going to take into account, and that is a speed limit.
سنضعها في الحسبان، ألا وهي حد السرعة.
Remember, the question was whether the car can drive fast or slow.
وكما تذكرون، كان السؤال هو ما إذا كان يمكن للسيارة أن تسير بسرعة أم ببطء.
So, if there's a speed limit, it shouldn't be driving very fast.
فإذا كان هناك حد للسرعة، ينبغي ألا تسير بسرعة فائقة.
So remember, before we had data that looked like this,
وكما تذكرون، كانت لدينا بيانات تبدو بهذا الشكل،
where he had the bumpiness and the grade.
حيث كان لدينا الوعورة والدرجة.
Now, let's suppose we had the speed limit and the grade.
الآن، لنفترض أن لدينا حد السرعة والدرجة.
And, let's suppose the speed limit worked like this.
ولنفترض أن حد السرعة يعمل بهذا الشكل.
If the speed limit was in force, you're in this half of the data.
إذا كان حد السرعة مُفعلاً، فسنكون في هذا النصف من البيانات.
And the, if the speed limit is not in force,
وإذا لم يكن الحد الأقصى للسرعة مُفعلاً،
you can go at whatever the speed you like, you're in this half of the data,
فسيمكننا القيادة بأية سرعة نرغب بها، وسنكون في هذا النصف من البيانات،
the lower half of the scatter plot here.
أي النصف السفلي من الرسم المبعثر هذا.
So then, when the speed limit is in effect, doesn't matter what grade it is,
إذن، إذا كان حد السرعة ساريًا، بغض النظر عن الدرجة،
everything's going to be slow.
فسيكون السير بطيئًا في جميع الأحوال.
Whereas, when the speed limit is not in effect,
بينما إذا لم يكن حد السرعة ساريًا،
you still have to go slow when it's too steep, but
فسيتعين أن تكون سرعة السيارة بطيئة عندما يكون الطريق منحدرًا للغاية، ولكن في هذه الحالة
now you can still go fast if it's flat enough, if the terrain is good.
لا يزال بالإمكان أن تزداد سرعة السيارة إذا كان الطريق مستويًا بصورة كافية، أو إذا كانت التضاريس جيدة.
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