Question 1
Decision trees is an example for?
- Supervised Machine Learning
- Unsupervised Machine Learning
- Semi-Supervised Machine Learning
- Reinforcement Learning
- Supervised Machine Learning
Question 2
Recommendation system and Anomaly detection are the applications of?
- Supervised Machine Learning
- Unsupervised Machine Learning
- Semi-Supervised Machine Learning
- Reinforcement Learning
2. Unsupervised Machine Learning
Question 3
Which of the following is used to overcome from the underfitting?
- Use data augmentation technique
- Remove outliers in the training set
- Add more features to the data
- Select a model with lesser features
3. Add more features to the data
Question 4
_____________are machine learning algorithms that first build a model from the training dataset before making any predictions on future datasets?
- Lazy learners
- Instance based learners
- Eager learners
- medium learners
3. Eager learners
Question 5
______________divides the data according to the likelihood that each dataset fits into a specific distribution?
- Partitioning Clustering
- Density-Based Clustering
- Hierarchical Clustering
- Distribution Model-Based Clustering
4. Distribution Model-Based Clustering
Question 6
Positive linear relationships are those where the dependent variable increases on the Y axis and the independent variable increases on the X axis?
- TRUE
- FALSE
- TRUE
Question 7
___________ is smaller than the training set and is used to assess how well models perform when given varied values for the hyperparameters?
- Training set
- Validation set
- Test set
- None of the above
2. Validation set
Question 8
____________is the amount that the estimate of the target function will change given different training data?
- Estimators
- Variance
- Bias
- None of the above
3. Bias
Question 9
___________uses Bayesian probability, to sum up proof for the likelihood of an expectation.?
- Statistical Inference
- Statistical Modeling
- Experiment Design
- All the above
- Statistical Inference
Question 10
The Hughes phenomenon claims that for a fixed size dataset, a machine learning model performs worse as dimensionality rises?
- TRUE
- FALSE
2. FALSE
If you find anything wrong in this Answer Key, feel free to reach us in the comment section.
q 10
false correct answer
Thank you . it has been updated
Q.no. 3
soln: (C) Add more features to the data
Q.no. 10
soln: False
Thank you . updated
The answer of que 3 and 10 is wrong
The right answer is
Ans 3 add more features to the data
Ans 10 false
Thank you . Updated
MODULE 04
QUIZ :
QUESTION: 03
Which of the following is used to overcome from the underfitting?
(a) Use data augmentation technique
(b)Remove outliers in the training set
(c)Add more features to the data
(d)Select a model with lesser features
correct ans: (c)
QUESTION: 10
The Hughes phenomenon claims that for a fixed size dataset, a machine learning model performs worse as dimensionality rises
(a)TRUE
(b)FALSE
correct ans: (b)
Thank you. It has been updated
I want to let you correct these two questions.
Question No. 3 correct answer is Option 3 Add more features to the data
Question No. 10 correct answer is Option 2 i.e. False
Thank you. updated