MCQ Questions - Boosting , SVM, PCA, Neural Network, Text Mining

 

Multiple Choice Questions for Data Science Practice Exams

MCQ Questions - Boosting , SVM, PCA, Neural Network, Text Mining

All MCQ Questions: https://www.algaestudy.com/search/label/MCQ

1. Boosting is a Sequential step process and works on weighted majority vote approach?

• Yes (correct)
• No
• Can’t Say
• None of these

2. Does Parameter C in SVM determine how many data samples are allowed to be placed in different classes?

• Yes (correct)
• No
• Can’t Say
• None of these

3. Is Association rules mining used in Recommender systems approach?

• Yes (correct)
• No
• Maybe
• Can't Say

4. The Cosine Similarity approach is used to predict only Movie Ratings?

• TRUE
• FALSE (correct)

5. What are all the steps comes under pre-processing in text mining 

1) Remove the stop words 

2) Tokenization 

3) Lemmatization 

4) Converting all the sentences into lower case

• 1 & 4 (correct)
• 1,2 & 4
• 2 & 3
• 1,2,3 & 4

6.Which approach is not used in recommendation system?

• Deep NN
• Regression method
• Matrix factorization (correct)
• Nearest-neighbor

7. What is TF-IDF abbreviation

• Term Frequent – Inverse document frequent
• Term Frequency – Invert document frequency
• Term Frequency – Inverse document frequency (correct)
• Term Frequency – Inverse documents frequency

8. Which does not comes under tree specific parameter in the Python

• n_estimators
• max_depth
• min_samples_split
• learning_rate (correct)

9. Which of the below sentence correct with respect to Text Mining & Text Analytics

• Text Analytics and Text mining both are same
• Text mining comes before text analytics
• Text analytics used for preprocessing of text and text mining used as input to Text analytics (correct)
• None of the above

10. Which is not correct w.r.to Boosting

• Boosting converts weak learner to strong learners
• It is used for reducing bias and variance in supervised learning.
• Boosting method also called as Bagging (correct)
• It is used to increase the accuracy of the Prediction in our model.

11.What is full form of PCA?

• Principal Component Analysis (correct)
• Principal Corrective Action
• Principal Component Action
• Principal Corrective Analysis

12. What is meant by Tokenization

• Tokens means individual sentences in the text
• Taking a text and breaking it up into its individual words. (correct)
• Splitting the punctuations and numbers separately from the text
• Removing rare words from the text

13. What is meant by TF (Term Frequency )

• (Number of times term T appears in the particular row) /(number of terms in that column)
• (Number of times term T appears in the particular row) / (number of terms in that row) (correct)
• (number of terms in that column) /(Number of times term T appears in the particular row)
• (number of terms in that row) / (Number of times term T appears in the particular row)

14. When we reduce the dimension in the data than the model takes less time to train a model ?

• Yes (correct)
• No
• Maybe
• Can't Say

15. What signifies about out-of-sample error in SVM?

• How far plane is to vector
• Threshold error in SVM
• Predict values for previously unseen data (correct)
• None of the above

16. Which is Dimensionality reduction technique?

• PCA (correct)
• LDA
• GDA
• SVM

17. Sentiment analysis also known as opinion mining

• TRUE (correct)
• FALSE
• Maybe
• Can't Say

18. SVM is a popular Unsupervised machine learning algorithm?

• TRUE
• FALSE (correct)
• Maybe
• Can't Say

19. Target variable is needed to define for applying dimensionality reduction algorithms on the data?

• TRUE (correct)
• FALSE
• Maybe
• Can't Say

All MCQ Questions: https://www.algaestudy.com/search/label/MCQ