WorksheetsNLP-B2-W5
Total questions: 10
Worksheet time: 5mins
In Kneser-Ney smoothing, what is the primary reason for using discounted probabilities in higher-order n-grams
To ensure that all n-grams, including unseen ones, receive some probability mass.
To reduce computational complexity in large language models.
To penalize frequent n-grams and favor less common ones.
To normalize the probability distribution so that it sums to one.
Which of the following is true about the backoff mechanism in Kneser-Ney smoothing?
It skips lower-order n-grams entirely if a higher-order n-gram has a non-zero probability.
It backs off to lower-order n-grams by subtracting a fixed discount and redistributing the remaining probability.
It only applies to n-grams that have been observed in the training data.
It applies a constant probability mass to all lower-order n-grams irrespective of their context.
In backoff smoothing technique, we use the bigrams if the evidence for trigram is insufficient.
TRUE
FALSE
Which of the following is a common application of the Naive Bayes classifier?
Predicting stock prices using time series analysis.
Spam detection in email filtering.
Real-time object detection in video streams.
Image classification tasks with large convolutional layers.
Which of the following types of data is the Naive Bayes classifier particularly well-suited for?
Data with a large number of missing values.
Data with categorical features where the independence assumption holds reasonably well.
Data with continuous features without any discretization.
Data with a high level of interaction between features.
Which of the following statements is true about the Naive Bayes classifier when applied to text classification tasks?
It requires feature scaling to work effectively in text classification
It cannot handle large vocabularies and is prone to overfitting
It is particularly effective because the independence assumption is often reasonably valid in the bag-of-words model
It is less effective than other classifiers due to its simplicity
Which of the following is the primary goal of a classification algorithm?
To assign input data to one of several predefined classes or categories
To reduce the dimensionality of the data
To group data points into clusters based on similarity
To predict a continuous output variable
Which of the following is an example of a binary classification problem?
Assigning a genre to a movie (e.g., action, comedy, drama)
Grouping customers into different segments based on purchasing behavior
Categorizing emails as "spam" or "not spam."
Predicting the price of a house based on its features
Which of the following is NOT a commonly used evaluation metric for classification models?
F1-Score
Precision
Mean Absolute Error (MAE)
Accuracy
Which classification algorithm is known for constructing decision boundaries by recursively splitting the feature space?
Decision Tree
Logistic Regression
k-Nearest Neighbors (k-NN)
Support Vector Machine (SVM)
