Which of the following correctly compares topic modeling and text classification?

Group counseling and individual counseling are effective treatment methods. 

Psychoanalysis is a short term treatment process. 

In client-centered therapy, the counselor will rely mostly on schedules of reinforcement. 

Gallium-arsenide lasers can be used to treat tendinopathies and osteoarthritis. 

Answer one of the following three questions about Old English poetry: 1. How does “The Dream of the Rood” present Christ as a new type of hero designed to resonate with Anglo-Saxon values and make Christianity appealing to a Northern warrior culture? Support your claims with specific details from the text. 2. What emotions does the female speaker in “The Wife’s Lament” communicate, and what caused these emotions? How are they conveyed through the poem’s language and imagery? Support your claims with specific details from the text. 3. How can comparing six translations of “Wulf and Eadwacer” enhance your understanding of the original poem’s meaning and the interpretive choices made by its translators? Use examples from multiple translations to illustrate your claims.

LDA requires labeled training data where each document is already categorized into predefined topics. ✅ False Explanation:LDA is an unsupervised learning method, meaning it does not require labeled data. Instead of assigning documents to predefined categories, it discovers hidden topics in the text by identifying word co-occurrence patterns.

Which of the following developed the psychosexual stages of development?

A company specializing in industrial equipment sales wants to analyze thousands of customer feedback messages to identify key complaint themes. They do not have predefined complaint categories but want to uncover patterns in the data. Which technique should they use? A) Sentiment analysisB) Named entity recognitionC) Latent Dirichlet Allocation (LDA)D) Supervised machine learning Answer: C) Latent Dirichlet Allocation (LDA) Explanation: LDA is a topic modeling technique that helps businesses identify hidden themes in large collections of unstructured text, such as customer complaints. Since the company does not have predefined categories, LDA is the best choice. Sentiment analysis (option A) determines emotional tone but does not uncover themes. Named entity recognition (option B) extracts specific entities (e.g., company names), not complaint topics. Supervised machine learning (option D) requires labeled data, which the company does not have.

Clients have autonomy within the counseling relationship.