1. What is Scikit-Learn?
a) A data visualization library
b) A machine learning library
c) A deep learning framework
d) An operating system
Answer: b) A machine learning library
2. Which of the following is not a core component of Scikit-Learn?
a) NumPy
b) Pandas
c) Matplotlib
d) Scipy
Answer: c) Matplotlib
3. Which of the following is a supervised learning algorithm in Scikit-Learn?
a) K-Means
b) Decision Trees
c) PCA
d) K-Nearest Neighbors
Answer: b) Decision Trees
4. What is the purpose of the fit method in Scikit-Learn?
a) To make predictions
b) To transform data
c) To train a model on data
d) To visualize data
Answer: c) To train a model on data
5. Which module in Scikit-Learn is used for feature selection and dimensionality reduction?
a) sklearn.neural_network
b) sklearn.preprocessing
c) sklearn.feature_selection
d) sklearn.metrics
Answer: c) sklearn.feature_selection
6. Which algorithm is commonly used for classification tasks in Scikit-Learn?
a) Linear Regression
b) K-Means
c) Random Forest
d) Principal Component Analysis (PCA)
Answer: c) Random Forest
7. In Scikit-Learn, what is the purpose of cross-validation?
a) To make predictions on unseen data
b) To split the dataset into training and test sets
c) To evaluate a model's performance on multiple data subsets
d) To fit a model to the training data
Answer: c) To evaluate a model's performance on multiple data subsets
8. Which of the following is an unsupervised learning algorithm in Scikit-Learn?
a) Logistic Regression
b) K-Means
c) Random Forest
d) Support Vector Machine (SVM)
Answer: b) K-Means
9. What is the purpose of the transform method in Scikit-Learn?
a) To fit a model to the data
b) To make predictions
c) To transform data based on a trained model
d) To evaluate model performance
Answer: c) To transform data based on a trained model
10. Which Scikit-Learn module is used for data preprocessing and scaling?
a) sklearn.preprocessing
b) sklearn.feature_selection
c) sklearn.ensemble
d) sklearn.metrics
Answer: a) sklearn.preprocessing
11. What does the term "hyperparameter" refer to in machine learning?
a) The final model's predictions
b) Parameters learned during model training
c) Parameters set before training, affecting model behavior
d) The number of data points in the training set
Answer: c) Parameters set before training, affecting model behavior
12. Which Scikit-Learn function is used to split a dataset into training and test sets?
a) train_test_split()
b) split_data()
c) divide_dataset()
d) test_train()
Answer: a) train_test_split()
13. Which of the following is a clustering algorithm in Scikit-Learn?
a) Linear Regression
b) K-Means
c) Decision Trees
d) Support Vector Machine (SVM)
Answer: b) K-Means
14. What is the purpose of the predict method in Scikit-Learn?
a) To evaluate a model's performance
b) To make predictions on new data
c) To transform data
d) To fit a model to the data
Answer: b) To make predictions on new data
15. Which metric is commonly used to evaluate the performance of a classification model in Scikit-Learn?
a) R-squared
b) Mean Absolute Error (MAE)
c) Accuracy
d) Mean Squared Error (MSE)
Answer: c) Accuracy
16. Which Scikit-Learn function is used to perform feature scaling, such as standardization or normalization?
a) scale_features()
b) normalize_data()
c) fit_transform()
d) StandardScaler()
Answer: d) StandardScaler()
17. Which Scikit-Learn module is used for regression tasks?
a) sklearn.cluster
b) sklearn.ensemble
c) sklearn.linear_model
d) sklearn.svm
Answer: c) sklearn.linear_model
18. What does the term "overfitting" mean in machine learning?
a) The model is too simple and doesn't capture the data's complexity
b) The model performs well on the training data but poorly on new data
c) The model is too complex and fits noise in the data
d) The model is not trained long enough
Answer: c) The model is too complex and fits noise in the data
19. Which Scikit-Learn algorithm is commonly used for text classification?
a) Decision Trees
b) Naive Bayes
c) K-Means
d) Principal Component Analysis (PCA)
Answer: b) Naive Bayes
20. What is the purpose of the fit_transform method in Scikit-Learn?
a) To fit a model to the data
b) To make predictions on new data
c) To evaluate model performance
d) To both fit and transform data
Answer: d) To both fit and transform data
21. Which Scikit-Learn algorithm is suitable for both regression and classification tasks?
a) K-Nearest Neighbors
b) Random Forest
c) Support Vector Machine (SVM)
d) Principal Component Analysis (PCA)
Answer: a) K-Nearest Neighbors
22. Which Scikit-Learn module is used for handling imbalanced datasets in classification?
a) sklearn.feature_selection
b) sklearn.metrics
c) sklearn.imbalanced
d) sklearn.svm
Answer: c) sklearn.imbalanced
23. What is the purpose of the GridSearchCV class in Scikit-Learn?
a) To perform hyperparameter tuning using cross-validation
b) To visualize data
c) To split the dataset into training and test sets
d) To fit a model to the data
Answer: a) To perform hyperparameter tuning using cross-validation
24. Which Scikit-Learn algorithm is commonly used for outlier detection?
a) Decision Trees
b) Linear Regression
c) Isolation Forest
d) Naive Bayes
Answer: c) Isolation Forest
25. What does the term "precision" refer to in the context of classification metrics?
a) The number of true positives
b) The number of true negatives
c) The number of false positives
d) The ability to correctly identify positive cases
Answer: a) The number of true positives
26. Which Scikit-Learn module is used for dimensionality reduction techniques like Principal Component Analysis (PCA)?
a) sklearn.decomposition
b) sklearn.cluster
c) sklearn.preprocessing
d) sklearn.ensemble
Answer: a) sklearn.decomposition
27. Which Scikit-Learn algorithm is known for its ability to handle high-dimensional data efficiently?
a) Random Forest
b) K-Means
c) Support Vector Machine (SVM)
d) Principal Component Analysis (PCA)
Answer: d) Principal Component Analysis (PCA)
28. What does the term "recall" refer to in the context of classification metrics?
a) The number of true positives
b) The number of true negatives
c) The number of false positives
d) The ability to correctly identify positive cases
Answer: d) The ability to correctly identify positive cases
29. Which Scikit-Learn algorithm is commonly used for ensemble learning and bagging techniques?
a) Decision Trees
b) Linear Regression
c) K-Means
d) Random Forest
Answer: d) Random Forest
30. What is the purpose of the roc_curve function in Scikit-Learn?
a) To calculate the Receiver Operating Characteristic (ROC) curve
b) To fit a model to the data
c) To make predictions on new data
d) To perform cross-validation
Answer: a) To calculate the Receiver Operating Characteristic (ROC) curve
31. Which Scikit-Learn module is used for natural language processing (NLP) tasks?
a) sklearn.nlp
b) sklearn.text
c) sklearn.language
d) There is no specific module; it's often done using other libraries like NLTK or spaCy.
Answer: d) There is no specific module; it's often done using other libraries like NLTK or spaCy.
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