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

#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