Bayes Rule DiagramYouTube↗  IA↗(long shot)
Education  22.8K views 32 likes 8 dislikes   23 Feb 2015
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ما قلناه بالفعل أن لدينا حالة تسمى prior
What we really said that we had a situation with prior
واختبارًا لحساسية محددة ودقة محددة.
a test, a certain sensitivity and a certain specificity.
عند تلقي نتيجة اختبار إيجابية فرضًا، ما نقوم به هو أخذ قيمة prior،
When you receive say a positive test result, what you do is you take your prior,
ونضربها في احتمالية نتيجة الاختبار هذه
you multiply in the probability of this test result.
في حالة وجود C، ونضربها في احتمالية نتيجة الاختبار في حالة عدم وجود C.
Given C, and you multiply in the probability of the test result given not C.
إذن، هذا هو الفرع المتعلق باعتبار الإصابة بالسرطان.
So this is your branch for the consideration that you have cancer.
وهذا هو الفرع المتعلق باعتبار عدم الإصابة بالسرطان.
This is your branch for the consideration you have no cancer.
عند الانتهاء من ذلك، نكون قد توصلنا لرقم يجمع بين فرضية الإصابة بالسرطان
When you're done with this, you arrive at a number that now combines the cancer
ونتيجة الاختبار.
hypothesis with the test result.
لكل من فرضية الإصابة بالسرطان وفرضية عدم الإصابة بالسرطان.
Both for the cancer hypothesis and the not cancer hypothesis.
ما سنقوم به الآن هو جمع هاتين القيمتين.
Now what you do, you add those up.
وعادة لا يكون مجموعهما واحدًا.
And they normally don't add up to one.
وسنحصل على قيمة معينة،
You get a certain quantity,
ألا وهي إجمالي الاحتمالية الخاصة بنتيجة الاختبار أيًا كانت.
which happens to be the total probability that the test is what it was.
وهي في هذه الحالة إيجابية.
This case positive.
كل ما علينا فعله بعد ذلك هو تنسيق هذه القيمة الموجودة هنا من خلال قسمتها
And all you do next is divide or
على حاصل الجمع هذا.
normalize this thing over here by the sum over here.
ويسري الأمر نفسه على الجانب الأيمن.
And the same on the right side.
يكون المقسوم هو ذاته
The divider is the same for
لكلا الحالتين نظرًا لأن هذا هو الفرع الخاص بالإصابة بالسرطان وهذا هو الفرع الخاص بعدم الإصابة بالسرطان.
both cases because this is your cancer range, your non cancer range.
لكن هذه القيمة لم تعد تعتمد على متغير السرطان بعد الآن.
But this guy doesn't rely on the cancer variable anymore.
ما وصلنا إليه الآن هو الاحتمالية اللاحقة المطلوبة
What you now get out is the desired posterior probability, and
ويكون مجموع ذلك واحدًا إذا أنجزت كل شيء بصورة صحيحة كما هو موضح هنا.
those add up to one if you did everything correct as shown over here.
وهذه هي الخوارزمية الخاصة بقاعدة بايز
This is your algorithm for Bayes Rule
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