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?

## Q:

### 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?

## Q:

### 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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