Lec-6.23 Logistic Regression Part-IV (Arif Butt @ Data Science)
01:10 Learning Agenda
02:43 Binary vs Multi-Class vs Multi-Label Classification
07:55 One vs Rest (aka One vs All)
14:00 Multinomial / Softmax Logistic Regression
23:31 Multi-Class Classification on iris Dataset
24:51 Load Dataset
29:50 Exploratory Data Analysis (EDA)
35:08 Model Training (ovr and multinomial Logistic Regression)
45:16 Evaluation Metrics for Multi-Class Classification
51:25 Confusion Matrix for Multi-Class Classifier
56:33 Accuracy, Precision, Recall and F-1 Scores for Multi-Class Problem¶
1:00:35 Macro Average Precision, Recall and F-1 Scores for Multi-Class Problem
1:02:11 Micro Average Precision, Recall and F-1 Scores for Multi-Class Problem
1:04:40 Weighted Average Precision, Recall and F-1 Scores for Multi-Class Problem
email: [email protected], [email protected], [email protected]
Lecture Slides and Resources: http://arifbutt.me
Jupyter notebooks: https://github.com/arifpucit/data-sci...