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)