Data Science Program Quiz 4

Data Science Quiz 4

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1. Which type of machine learning algorithm is used to predict continuous numerical values?

Clustering

Reinforcement Learning

Regression

Classification

2. Which of the following is a key difference between classification and regression?

Classification is always unsupervised, while regression is always supervised

Classification deals with labeled data, while regression does not

Regression predicts categorical outcomes, while classification predicts numerical values

Regression predicts numerical values, while classification predicts categorical outcomes

3. Which machine learning library is commonly used in Python for building models efficiently?

Pandas

Scikit-learn

TensorFlow

Matplotlib

4. Which metric is best suited for evaluating a classification model on an imbalanced dataset?

Accuracy

Mean Squared Error (MSE)

Root Mean Squared Error (RMSE)

F1-score

5. In Scikit-learn, which function is used to split a dataset into training and testing sets?

model_split

train_test_split

data_split

split_dataset

6. Which of the following is an example of a supervised learning algorithm?

t-SNE

Principal Component Analysis (PCA)

Support Vector Machine (SVM)

K-Means

7. Which evaluation metric is most appropriate when false positives and false negatives carry different costs?

Mean Absolute Error

Accuracy

Precision and Recall

R-squared

8. What is the primary purpose of feature scaling in machine learning?

Improve data visualization

Increase dataset dimensionality

Ensure features contribute equally to the model

Reduce dataset size

9. Which of the following is not a common step in building a machine learning model?

Feature extraction

Data preprocessing

Database indexing

Hyperparameter tuning

10. Which function in Scikit-learn is used to evaluate a classification model’s accuracy?

log_loss()

r2_score()

mean_squared_error()

accuracy_score()

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Data Science Program Quiz 4

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