Machine Learning
Explore essential machine learning concepts including accuracy, recall, precision, dimensionality reduction, SVM, clustering, distance measures, and common algorithms. Understand their applications and implications to build a solid foundation for data science interviews.
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What do you understand by accuracy, recall, and precision?
Consider that we have to predict a dichotomous variable that has "yes" and "no" responses, as shown below:
Confusion matrix
Predicted | |||
no | yes | ||
Actual | no | 9800 | 100 |
yes | 30 | 70 | |
There were 9,000 "no" responses in the data and 100 "yes" responses. Accuracy is the percentage of correct predictions of positive and negative responses. Considering "yes" as a positive response and "no" as a negative response, the accuracy will be (9800+70)/10000 = 98.7%.
The recall is the percentage of positive responses predicted correctly out of the total positive ...