>>>>>>Data Scientist Tricky Interview Questions
Examples of Parametric machine learning algorithm and non-parametric machine learning algorithm
Parametric machine learning algorithm– Linear Regression, Logistic Regression Non-Parametric machine learning algorithm – Decision Trees, SVM, Neural Network
What are parametric and non-parametric machine learning algorithm? And their importance
The algorithm which does not make strong assumptions are a non-parametric algorithm and they are free to learn from training data. The algorithm that makes strong assumptions are parametric and it involves
select the form for the function and learn the coefficients
When does linear and logistic regression performs better, generally?
It works better when we remove the attributes which are unrelated to the output variable and highly co-related variable to each other.
Give some example for false positive, false negative, true positive, true negative
False Positive – A cancer screening test comes back positive, but you don’t have cancer
False Negative – A cancer screening test comes back negative, but you have cancer
True Positive – A Cancer Screening test comes back positive, and you have cancer
True Negative – A Cancer Screening test comes back negative, and you don’t have cancer
What is Sensitivity and Specificity?
Sensitivity means “proportion of actual positives that are correctly classified” in other words “True Positive”
Specificity means “proportion of actual negatives that are correctly classified” “True Negative”