#10 ROC curve with AUC, Sensitivity & Specificity | Multinomial Logistic Regression in R

Week-10 R and data Files:
https://github.com/bkrai/Statistical-...
TIMESTAMPS
00:00 Logistic regression
02:00 Confusion matrix, Accuracy, Sensitivity, Specificity
05:15 Baseline rate
10:35 Effect of change in threshold or cutoff
15:40 ROC Curve
21:16 Area under curve (AUC)
23:00 Working with R
26:25 Confusion matrix from logistic regression model
29:14 ROC curve in R
34:30 ROC curve with AUC, best threshold, sensitivity & specificity
37:00 Best threshold & AUC
38:00 Two ROC curves on the same plot
43:10 Why logistic regression? Why linear regression doesn't work for factor type response?
01:00:39 CTG data & Multinomial logistic regression
01:03:02 Independent and dependent variables
01:03:39 Probability equations for multinomial logistic regression model
01:06:24 Model interpretation, coefficients, standard errors & 2-tailed z test
01:12:48 Writing the equation
01:15:06 Confusion matrix and related metric
01:15:41 multinomial logistic regression in R
01:34:30 Multi-class ROC Curves

R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.

#MultinomialLogistic #MachineLearning