15. Data Analysis (Classification Algorithms) - Big-Data Analytics
من بداية الدقيقة 27:34 في تصحيح مهم
الجداول الموجوده في سلايد 76 فيها ارقام غلط ومش هي اللي هستخدمها في المعادله الموجوده
المفروض ال P(sunny|Yes) معناه انه عايز ال probability بتاعت sunny لما يكون yse متحققه
P(sunny|Yes) means the probability of observing the attribute "sunny" given that the target variable "play tennis" is "Yes"
يعني المفروض P(sunny|Yes) تساوي 2/9 عشان sunny اتحققت مرتين بس خلال ال9 مرات بتوع ال yes
و P(cool|Yes) تساوي 3/9 عشان ال cool اتحققت 3 مرات خلال ال9 مرات بتوع ال yes
وهكذا ...
يعني المعادلات النهائية المفروض تبقى
V(Yes) = 9/14 * 2/9 * 3/9 * 3/9 * 3/9 = 0.00529
V(No) = 5/14 * 3/5 * 1/5 * 4/5 * 3/6 = 0.02057
وتكمل عادي اخر خطوة
0:00 What is Classification Analysis?
3:11 Linear Models - Logistic Regression
12:08 Linear Models - Support Vector Machines (SVM)
17:44 Non-Linear Models - K-Nearest Neighbors (KNN)
23:04 Non-Linear Models - Naive Bayes
27:34 Check the Description or Comments...
29:37 Non-Linear Models - Naive Bayes (Cont.)
31:44 Non-Linear Models - Decision Tree Classifier
50:20 Non-Linear Models - Random Forest
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