I want to create a multiple choice test of 10 questions to screen for machine learning skill. 

Topics should include binary classification using logistic regression or GDBT. Encoding categorical variables. Testing the understanding of classification metrics. 

Then additional topics are regression and basic statistics. 

Can you give me a list of ten questions?2 / 2
user
Sure, here are 10 questions based on your requirements:

1. Which machine learning algorithm is commonly used for binary classification?
   - A. Naive Bayes
   - B. Random Forest
   - C. Decision Trees
   - D. Logistic Regression
   - E. Support Vector Machines (SVM)

2. Which of the following is a binomial random variable?
   - A. Rolling a six-sided dice
   - B. Flipp a coin ten times
   - C. Measuring the height of people in a classroom
   - D. All of the above

3. Which of the following is an example of a categorical feature?
   - A. Age
   - B. Gender
   - C. Income
   - D. Both B and C

4. Which machine learning algorithm is best suited for handling classification imbalance?
   - A. Naive Bayes
   - B. Random Forest
   - C. Gradient Boosting Decision Trees (GBDT)
   - D. Discriminative Training
   - E. K-Nearest Neighbors (KNN)

5. Which metric is used to measure the accuracy of binary classification?
   - A. True Positive Rate (TPR)
   - B. True Negative Rate (TNR)
   - C. F1-Score
   - D. Precision

6. Which of the following is used for grouping categorical variables?
   - A. Bucketization
   - B. Embedding
   - C. Labelling
   - D. Discretization

7. What is the purpose of scale normalization in machine learning?
   - A. To improve model performance
   - B. To shrink values
   - C. To provide insight into the differences between individual observations
   - D. All of the above

8. Which algorithm is usually slower in terms of training time but always gives the best model performance?
   - A. Logistic Regression
   - B. Decision Tree
   - C. Support Vector Machines (SVM)
   - D. Gradient Boosting Decision Trees (GBDT)

9. Which machine learning task focuses on learning decision rules that enable classifications or decisions?
   - A. Regression
   - B. Clustering
   - C. Anomaly Detection
   - D. Classification

10. Which algorithm trains an ensemble of decision trees?
   - A. Random Forest
   - B. Support Vector Machines (SVM)
   - C. Multi-Layer Perceptron (MLP)
   - D. Gradient Boosting Decision Trees (GDBT)

I hope these questions help you to screen for "Machine Learning skill." However, I would like to clarify that these questions only cover a few topics; they are not comprehensive tests. They are created based on your requirements, so they do not cover all aspects of machine learning. If you need questions to test several aspects, I can create them, but I may add interest to the MLA format.
assistant
I want to create a multiple choice test of 10 questions to screen for machine learning skill. 

Topics should include binary classification using logistic regression or GDBT. Encoding categorical variables. Testing the understanding of classification metrics. 

Then additional topics are regression and basic statistics. 

Can you give me a list of ten questions?2 / 2
user
Sure, here are ten multiple choice questions that cover the topics you mentioned:

1. Which of the following is a common technique for encoding categorical variables in a machine learning model?
(a) One-hot encoding
(b) Mean encoding
(c) Label encoding
(d) All of the above
2. In binary classification using logistic regression, which of the following is used as the activation function?
(a) Sigmoid function
(b) ReLU function
(c) Softmax function
(d) Tanh function
3. In binary classification, which of the following metrics is used to measure the proportion of actual negatives that are correctly identified as such?
(a) Precision
(b) Recall
(c) Specificity
(d) F1 Score
4. In gradient boosting decision trees (GDBT), which of the following is used to minimize the loss function?
(a) Gradient descent
(b) Stochastic gradient descent
(c) Newton's method
(d) Coordinate descent
5. Which of the following is a common evaluation metric for imbalanced classification datasets?
(a) Accuracy
(b) Precision
(c) Recall
(d) F1 Score
6. Which of the following is a measure of how spread out the data is in a dataset?
(a) Mean
(b) Median
(c) Standard deviation
(d) Interquartile range
7. In linear regression, which of the following assumptions is made about the residuals?
(a) They are normally distributed
(b) They have constant variance
(c) They are independent
(d) All of the above
8. Which of the following is a measure of the strength and direction of a linear relationship between two variables?
(a) Correlation coefficient
(b) Covariance
(c) Slope
(d) Intercept
9. Which of the following is a common technique for selecting the most important features in a dataset?
(a) Principal component analysis (PCA)
(b) Recursive feature elimination (RFE)
(c) Lasso regression
(d) All of the above
10. Which of the following is a measure of how well a machine learning model generalizes to new data?
(a) Training accuracy
(b) Test accuracy
(c) Cross-validation accuracy
(d) Overfitting

Answers: 1(d), 2(a), 3(c), 4(a), 5(d), 6(c), 7(d), 8(a), 9(b), 10(c)
assistant