Q. In regression analysis, what does the term 'overfitting' refer to?
A.
The model performs well on training data but poorly on unseen data
B.
The model is too simple to capture the underlying trend
C.
The model has too few features
D.
The model is perfectly accurate
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Solution
Overfitting occurs when a model learns the training data too well, capturing noise instead of the underlying pattern, leading to poor performance on unseen data.
Correct Answer:
A
— The model performs well on training data but poorly on unseen data
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Q. In regression tasks, which metric is typically used to measure the difference between predicted and actual values?
A.
F1 Score
B.
Mean Absolute Error
C.
Confusion Matrix
D.
Precision
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Solution
Mean Absolute Error (MAE) is used in regression tasks to quantify the average absolute difference between predicted and actual values.
Correct Answer:
B
— Mean Absolute Error
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Q. What type of problem is predicting house prices based on features like size and location?
A.
Classification
B.
Regression
C.
Clustering
D.
Dimensionality Reduction
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Solution
Predicting house prices is a regression problem, as it involves predicting a continuous numerical value based on input features.
Correct Answer:
B
— Regression
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Q. What type of supervised learning problem is predicting house prices?
A.
Classification
B.
Regression
C.
Clustering
D.
Dimensionality Reduction
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Solution
Predicting house prices is a regression problem because it involves predicting a continuous numerical value.
Correct Answer:
B
— Regression
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Q. Which algorithm is commonly used for binary classification problems?
A.
K-Means Clustering
B.
Linear Regression
C.
Logistic Regression
D.
Principal Component Analysis
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Solution
Logistic Regression is a widely used algorithm for binary classification tasks, modeling the probability of a binary outcome.
Correct Answer:
C
— Logistic Regression
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Q. Which of the following is a common algorithm used for classification tasks?
A.
Linear Regression
B.
Logistic Regression
C.
K-Means Clustering
D.
Principal Component Analysis
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Solution
Logistic Regression is commonly used for classification tasks as it predicts the probability of a binary outcome.
Correct Answer:
B
— Logistic Regression
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Q. Which of the following is a common evaluation metric for classification problems?
A.
Mean Squared Error
B.
Accuracy
C.
R-squared
D.
Silhouette Score
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Solution
Accuracy is a common metric used to evaluate the performance of classification models by measuring the proportion of correct predictions.
Correct Answer:
B
— Accuracy
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Q. Which of the following techniques can help prevent overfitting in supervised learning?
A.
Increasing the complexity of the model
B.
Using more training data
C.
Reducing the number of features
D.
All of the above
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Solution
Using more training data can help prevent overfitting by providing a more comprehensive representation of the underlying data distribution.
Correct Answer:
B
— Using more training data
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