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Healthcare Informatics (HCIF) > ML Foundation Set 1 (Answers) > Flashcards

ML Foundation Set 1 (Answers) Flashcards

1
Q

Among the following option identify the one which is NOT a type of learning?

a) Semi unsupervised learning
b) Supervised learning
c) Reinforcement learning
d) Unsupervised learning

A

a) Semi unsupervised learning

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2
Q

Identify the kind of learning algorithm for “facial identities for facial expressions”.

a) Prediction
b) Recognise patterns
c) Recognising anomalies
d) Generating patterns

A

b) Recognise patterns

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3
Q

Identify the model which is trained with data in only a single batch.

a) Offline learning
b) Batch learning
c) Both A and B
d) None

A

c) Both offline learning and batch learning

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4
Q

What is the application of machine learning methods to a large database called?

a) Big data computing
b) Internet of things
c) Data mining
d) Artificial intelligence

A

c) Data mining

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5
Q

Identify the type of learning in which labeled training data is used.

a) Semi unsupervised learning
b) Supervised learning
c) Reinforcement learning
d) Unsupervised learning

A

b) Supervised learning

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6
Q

In Principal Component Analysis (PCA) the number of input dimensions is equal to principal components. True or False?

A

True

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7
Q

Among the following identify the one in which dimensionality reduction reduces.

a) Performance
b) Entropy
c) Stochastics
d) Collinearity

A

d) Collinearity

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8
Q

Which of the following machine learning algorithm is based upon the idea of bagging?

a) Decision tree
b) Random forest
c) Classification
d) Regression

A

b) Random forest

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9
Q

Choose a disadvantage of decision trees:

a) Decision trees are robust to outliers
b) Factor analysis
c) Decision trees are prone to overfit
d) All of the above

A

c) Decision trees are prone to overfitting

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10
Q

What is the term known as on which the machine learning algorithms build a model based on sample data?

a) Data training
b) Training data
c) Transfer data
d) None of the above

A

b) Training data

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11
Q

Machine learning is a subset of which of the following.

a) Artificial intelligence
b) Deep learning
c) Data learning
d) None of the above

A

a) Artificial intelligence

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12
Q

Which of the following machine learning techniques helps in detecting the outliers in data?

a) Classification
b) Clustering
c) Anatomy detection
d) All of the above

A

c) Anatomy detection

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13
Q

The father of machine learning is _____________

a) Geoffrey Everest Hinton
b) Geoffrey Hill
c) Geoffrey Chaucer
d) None of the above

A

a) Geoffrey Everest Hinton

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14
Q

The most significant phase in genetic algorithm is _________

a) Mutation
b) Selection
c) Fitness function
d) Crossover

A

d) Crossover

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15
Q

Which of the following are common classes of problems in machine learning?

a) Regression
b) Classification
c) Clustering
d) All of the above

A

d) All of the above

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16
Q

Among the following options identify the one which is FALSE regarding regression.

a) It is used for prediction
b) It is used for interpretation
c) It relates inputs to outputs
d) It discovers casual relationships

A

d) It discovers casual relationships

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17
Q

Identify the successful applications of ML.

a) Learning to classify new astronomical structures
b) Learning to recognize spoken words
c) Learning to drive an autonomous vehicle
d) All of the above

A

d) All of the above

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18
Q

Identify the incorrect numerical functions in the various function representation of machine learning.

a) Case-based
b) Support vector machines
c) Linear regression
d) Neural network

A

a) Case-based

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19
Q

FIND-S algorithm ignores?

a) Positive
b) Negative
c) Both
d) None

A

b) Negative

20
Q

Select the correct definition of neuro software.

a) It is software used by neurosurgeons
b) It is software used to analyze neurons
c) It is a powerful and easy neural network
d) None of the above

A

c) It is a powerful and easy neural network

21
Q

The backpropagation law is also known as the
generalized Delta rule. True or False?

A

True

22
Q

Choose the general limitations of the backpropagation rule among the following.

a) Slow convergence
b) Scaling
c) Local minima problem
d) All of the above

A

d) All of the above

23
Q

Analysis of ML algorithm needs?

a) Statistical learning theory
b) Computational learning theory
c) Both A and B
d) None of the above

A

c) Both statistical learning theory and computational learning theory

24
Q

Choose the most widely used mattress and tools to assess the classification models.

a) The area under the ROC curve
b) Confusion matrix
c) Cost-sensitive accuracy
d) All of the above

A

d) All of the above

25
Q

Full form of PAC is _____________

a) Probably Approximate Cost
b) Probably Approximate Correct
c) Probably Approximate Communication
d) Probably Approximate Computation

A

b) Probably Approximate Correct

26
Q

True error is defined over the entire instance space, and not just over training data. True or False?

A

True

27
Q

Choose the options below of which the area CLT is comprised of.

a) Mistake bound
b) Sample complexity
c) Computational complexity
d) All of the above

A

d) All of the above

28
Q

Choose the instance-based learner.

a) Eager learner
b) Lazy learner
c) Both A and B are correct
d) None of the above

A

b) Lazy learner

29
Q

Identify the difficulties with the k-nearest neighbor algorithm.

a) Curse of dimensionality
b) Calculate the distance of the test case from all training cases
c) Both A and B
d) None of the above

A

c) Both A and B

30
Q

The total types of the layer in radial basis function neural networks is ______

a) 1
b) 2
c) 3
4) 4

A

c) 3

31
Q

Which of the following is an application of Case-based reasoning (CBR)?

a) Diagnosis
b) Design
c) Planning
d) All of the above

A

b) Design

32
Q

Choose the correct advantages of CBR.

a) Fast to train
b) A local approximation is found for each test case
c) Knowledge is in a form understanding by human
d) All of the above

A

d) All of the above

33
Q

Machine learning as various Search and Optimisation algorithms. Identify among the following which is NOT evolutionary computation.

a) Genetic algorithm
b) Generic programming
c) Neuroevolution
d) Perception

A

d) Perception

34
Q

Artificial intelligence is the process that allows a computer to learn
and make decisions like humans. True or False?

A

True

35
Q

Which of the following is not machine learning disciplines?

a) Information theory
b) Optimisation + control
c) Physics
d) Neuro statistics

A

d) Neuro statistics

36
Q

What does K stand for in K mean algorithm?

a) Number of clusters
b) Number of data
c) Number of attributes
d) Number of iterations

A

a) Number of clusters

37
Q

Decision tree cannot be used for clustering. True or False?

A

False

38
Q

Identify the clustering method which takes care of variance in data.

a) Decision tree
b) Gaussian mixture model
c) K means
d) All of the above

A

b) Gaussian mixture model

39
Q

Which of the following is NOT a supervised learning?

a) PCA
b) Naïve Bayesian
c) Linear regression
d) Decision tree

A

a) PCA

40
Q

What is unsupervised learning?

a) Number of groups may be known
b) Features of group explicitly stated
c) Neither feature nor number of groups is known
d) None of the above

A

c) Neither feature nor number of groups is known

41
Q

Which of the following is not a machine learning algorithm?

a) Support Vector Machine (SVM)
b) Scalable Vector Graphics (SVG)
c) Random Test
d) None of the above

A

b) SVG

42
Q

What is true about Machine Learning?

a) Artificial intelligence
b) Rule-based inference
c) Both A and B
d) None of the above

A

c) Both artificial intelligence and rule-based inference

43
Q

Which of the following is not machine learning?

a) Artificial intelligence
b) Rule-based inference
c) Both A and B
d) None of the above

A

b) Rule-based inference

44
Q

Identify the method which is used for trainControl resampling.

a) svm
b) repeatedcv
c) Bag32
d) None of the above

A

b) repeatedcv

45
Q

Among the following option identify the one which is used to create the most common graph types.

a) Plot
b) Quickplot
c) Qplot
d) All of the above

A

c) Qplot

Healthcare Informatics (HCIF) (12 decks)

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