Practice More Questions From: Predicting sentiment from product reviews
Q:
How many weights are greater than or equal to 0?
Q:
Of the three data points in sample_test_data, which one has the lowest probability of being classified as a positive review?
Q:
Which of the following products are represented in the 20 most positive reviews?
Q:
Which of the following products are represented in the 20 most negative reviews?
Q:
What is the accuracy of the sentiment_model on the test_data? Round your answer to 2 decimal places (e.g. 0.76).
Q:
Does a higher accuracy value on the training_data always imply that the classifier is better?
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Consider the coefficients of simple_model. There should be 21 of them, an intercept term + one for each word in significant_words. How many of the 20 coefficients (corresponding to the 20 significant_words and excluding the intercept term) are positive for the simple_model?
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Are the positive words in the simple_model also positive words in the sentiment_model?
Q:
Which model (sentiment_model or simple_model) has higher accuracy on the TRAINING set?
Q:
Which model (sentiment_model or simple_model) has higher accuracy on the TEST set?
Q:
Enter the accuracy of the majority class classifier model on the test_data. Round your answer to two decimal places (e.g. 0.76).
Q:
Is the sentiment_model definitely better than the majority class classifier (the baseline)?
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