Top 15 Evaluation Metrics for Machine Learning with Examples
https://www.machinelearningplus.com/machine-learning/evaluation-metrics-classification-models-r/
Introduction: Building The Logistic ModelThe Confusion MatrixHow to Interpret Caret’s Confusionmatrix?What Is Sensitivity, Specificity and Detection Rate?What Is Precision, Recall and F1 Score?What Is Cohen’s Kappa?What Is KS Statistic and How to Interpret KS Chart?How to Plot Kolmogorov Smirnov Chart in R?How to Interpret Roc curve?Concordance and DiscordanceSensitivity is the percentage of actual 1’s that were correctly predicted. It shows what percentage of 1’s were covered by the model. The total number of 1’s is 71 out of which 70 was correctly predicted. So, sensitivity is 70/71 = 98.59% Sensitivity matters more when classifying the 1’s correctly is more important than classifying the 0’s. Just li...See more on machinelearningplus.comReviews: 6Estimated Reading Time: 8 minsAuthor: Selva PrabhakaranPublished: Sep 30, 2017Missing: definitionMust include: definitionExplore further Sensitivity is the percentage of actual 1’s that were correctly predicted. It shows what percentage of 1’s were covered by the model. The total number of 1’s is 71 out of which 70 was correctly predicted. So, sensitivity is 70/71 = 98.59% Sensitivity matters more when classifying the 1’s correctly is more important than classifying the 0’s. Just li... Reviews: 6 Published: Sep 30, 2017 definition
Sensitivity is the percentage of actual 1’s that were correctly predicted. It shows what percentage of 1’s were covered by the model. The total number of 1’s is 71 out of which 70 was correctly predicted. So, sensitivity is 70/71 = 98.59% Sensitivity matters more when classifying the 1’s correctly is more important than classifying the 0’s. Just li...
Reviews: 6
Published: Sep 30, 2017
definition
DA: 61 PA: 80 MOZ Rank: 32
