False Positive More Important

Question: Can you cite an example of when a false positive is more important than a false negative? False positive is when you wrongly classified…

Unsupervised Learning

Question: What is unsupervised learning? This means the data is not labeled ahead of time for the algorithm. Used to analyze data to make sense…

Supervised Learning

Question: What is supervised learning? This means the data is pre-labeled for the algorithm. Helps when predicting from data we already identified. Example: Supervised machine…

Machine Learning

Question: What is machine learning? It’s a broadly used term, so think of good examples from your industry. This includes prediction and analysis. Example: Machine…

Cross-Validation

Question: Explain cross-validation.  Cross validation evaluates if the outcomes will generalize to another data set. Good for estimating the accuracy of a model. Example: I…

Validation Set vs Test Set

Question: Can you explain the difference between a validation set and a test set? This is when you’re checking for over-fitting and parameter selection. The…

False Negative More Important

Question: Can you cite an example of when a false negative is more important than a false positive? False negative is where you wrongly classify…

False Errors Equally Important

Question: Can you cite an example where false negatives and false positives are equally important? Review the definition of each, both false positive and false…

Logistic Regression

Question: What is logistic regression? This will have a binary outcome. Usually predicting the odds of that outcome using predictor variables. Example: Logistic regression is…

Various Classification Algorithms

Question: What are the various classification algorithms? There are quite a few, so list the ones you know. There are subcategories you could mention, too.…