Online Access Free AIP-210 Practice Test

You have a dataset with thousands of features, all of which are categorical. Using these features as predictors, you are tasked with creating a prediction model to accurately predict the value of a continuous dependent variable. Which of the following would be appropriate algorithms to use? (Select two.)

• A.K-means
• B.Ridge regression
• C.Lasso regression
• D.K-nearest neighbors
• E.Logistic regression

We are using the k-nearest neighbors algorithm to classify the new data points. The features are on different scales.
Which method can help us to solve this problem?

• A.Square-root transformation
• B.Normalization
• C.Log transformation
• D.Standardization

Which type of regression represents the following formula: y = c + b*x, where y = estimated dependent variable score, c = constant, b = regression coefficient, and x = score on the independent variable?

• A.Linear regression
• B.Polynomial regression
• C.Ridge regression
• D.Lasso regression

Which of the following is NOT a valid cross-validation method?

• A.Bootstrapping
• B.Leave-one-out
• C.Stratification
• D.K-fold

Which of the following algorithms is an example of unsupervised learning?

• A.Principal components analysis
• B.Neural networks
• C.Ridge regression
• D.Random forest