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  5. CS607 Quiz #2 Solution and Discussion

CS607 Quiz #2 Solution and Discussion

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zaasmi
zaasmi
Cyberian's Gold

Please share your current Quiz and Solution to help the students…

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zaasmi
zaasmi
Cyberian's Gold

Hypothesis space uses the ________________ of the attributes. CS607

conjunctions (AND) (Page No 168)

91bd86e3-fba3-4132-885c-4bb3c224f37f-image.png

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zaasmi
zaasmi
Cyberian's Gold

Which one is NOT the phase of machine learning: CS607

a7dbc9d9-1f53-4ac9-bcbe-cb883f7b1b3c-image.png

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zaasmi
zaasmi
Cyberian's Gold

In theoretical computer science there are two main branches of problems: CS607

• Tractable
• Intractable
Page (165)
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zaasmi
zaasmi
Cyberian's Gold

The Entropy is 1 when the collection contains number of positive examples _______ to/than negative examples. CS607
Equal (Page 177)

6f0a4a18-deea-4521-af71-5f23e697cba9-image.png

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zaasmi
zaasmi
Cyberian's Gold

The first step of FIND-S is to initialize h to the most specific hypothesis in __________: h = < Ø , Ø > CS607

H (Page 172)

56068d58-c7bf-4e43-8b57-929b4a0328a4-image.png

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zaasmi
zaasmi
Cyberian's Gold

Decision trees give us disjunctions of conjunctions, that is, they have the form:(A AND B) _______ (C AND D). CS607

OR (Page 176)

89cd8e9d-2603-4ae9-8293-65622c498633-image.png

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zaasmi
zaasmi
Cyberian's Gold

________ stands for interactive dichotomizer CS607
ID (Page No. 177)

476b9779-e6b0-46fd-9227-259ce6468eab-image.png

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zaasmi
zaasmi
Cyberian's Gold

Interactive Dichotomizer uses a special function ________, to evaluate the gain information of each attribute. CS607
Page 177

cad37080-6f90-4393-b199-6d6cda5aa1a2-image.png

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zaasmi
zaasmi
Cyberian's Gold

_____________ learning works on existing facts and knowledge and deduces new knowledge from the old. CS607

Deductive (Page 162)
9026ed53-e3b6-40cb-8e11-ee5ec18ae7cc-image.png

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zaasmi
zaasmi
Cyberian's Gold

Machine learning typically follows ___________ phases according to Finlay. CS607

Three (Page 160)
b9e3c417-49de-4df6-9d32-db315dc9fea0-image.png

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cyberian
cyberian
Cyberian's

Question # 1 of 10 ( Start time: 08:34:53 PM ) Total Marks: 1

The Entropy is 1 when the collection contains number of positive examples _______ to/than negative examples.

Select correct option:

Equal

Greater

Less

None of the given

Question # 2 of 10 ( Start time: 08:35:22 PM ) Total Marks: 1

Measure of the effectiveness of an attribute in classifying the training data is called.

Select correct option:

Information Gain

Measure Gain

Information Goal

None of the given

Question # 3 of 10 ( Start time: 08:36:15 PM ) Total Marks: 1

A drawback of FIND-S is that, it assumes the consistency within the training set.

Select correct option:

True

False

Question # 4 of 10 ( Start time: 08:37:03 PM ) Total Marks: 1

The brain is a collection of about 100 ________ interconnected neurons.

Select correct option:

Million

Billion

Trillion

None of the given

Question # 5 of 10 ( Start time: 08:37:52 PM ) Total Marks: 1

Hypothesis space uses the ________________ of the attributes.

Select correct option:

Conjunctions (AND)

Disjunctions (OR)

Negation (NOR)

None of the given

Question # 6 of 10 ( Start time: 08:38:44 PM ) Total Marks: 1

Aggregation only occurs once for each output variable, just after the fifth and final step, defuzzification.

Select correct option:

True

False

Question # 7 of 10 ( Start time: 08:39:48 PM ) Total Marks: 1

A concept is the representation of the __________ with respect to the given attributes.

Select correct option:

Solution

Problem

Knowledge

None of the given

Question # 8 of 10 ( Start time: 08:40:32 PM ) Total Marks: 1

__________ is the process by which the fuzzy sets that represent the outputs of each rule are combined into a single fuzzy set.

Select correct option:

Aggregation

Fuzzification

Implication

None of the given

Question # 9 of 10 ( Start time: 08:41:22 PM ) Total Marks: 1

The first step of FIND-S is to initialize h to the most specific hypothesis in __________: h = < Ø , Ø >

Select correct option:

H

I

J

K

Question # 10 of 10 ( Start time: 08:42:19 PM ) Total Marks: 1

A single Perceptron simply draws a line, which is a hyper plane when the data is _____ than 2 dimensional.

Select correct option:

More

Less

Equal

None of the given

Quiz-2

Question # 1 of 10 ( Start time: 08:44:17 PM ) Total Marks: 1

Complex problems usually have well-defined steps

Select correct option:

True

False

Question # 2 of 10 ( Start time: 08:45:47 PM ) Total Marks: 1

__________ is the process by which the fuzzy sets that represent the outputs of each rule are combined into a single fuzzy set.

Select correct option:

Aggregation

Fuzzification

Implication

None of the given

Question # 3 of 10 ( Start time: 08:46:05 PM ) Total Marks: 1

The first step of FIND-S is to initialize h to the most specific hypothesis in __________: h = < Ø , Ø >

Select correct option:

H

I

J

K

Question # 4 of 10 ( Start time: 08:46:19 PM ) Total Marks: 1

Choose the fields in which Fuzzy inference systems have been successfully applied:

Select correct option:

automatic control

data classification

decision analysis

All of the given

Question # 5 of 10 ( Start time: 08:47:13 PM ) Total Marks: 1

A concept is the representation of the __________ with respect to the given attributes.

Select correct option:

Solution

Problem

Knowledge

None of the given

Question # 6 of 10 ( Start time: 08:47:30 PM ) Total Marks: 1

_________ is the process of formulating the mapping from a given input to an output using Fuzzy logic.

Select correct option:

FIZ

FIS

FOS

None of the given

Question # 7 of 10 ( Start time: 08:48:11 PM ) Total Marks: 1

The input of the aggregation process is the list of truncated output functions returned by the _________ process for each rule.

Select correct option:

Truncation

Implication

Aggregation

None of the given

Question # 8 of 10 ( Start time: 08:49:09 PM ) Total Marks: 1

In Fuzzy Inputs we resolve all fuzzy statements in the antecedent to a degree of membership between 0 and _____

Select correct option:

1

2

3

4

Question # 9 of 10 ( Start time: 08:49:37 PM ) Total Marks: 1

Fuzzy inference systems (FIS) are NOT associated with a number of names.

Select correct option:

True

False

Question # 10 of 10 ( Start time: 08:50:16 PM ) Total Marks: 1

Inductive learning takes examples and generalizes rather than starting with __________ knowledge.

Select correct option:

Existing

Inductive

Deductive

None of the given

Quiz-3

1-Artificial Neural Networks is a new learning paradigm which takes its roots from _________ inspired approach to learning.

Biology

2- In Candidate-Elimination algorithm version space is represented by two sets named:

G and S

3-Interactive Dichotomizer uses a special function ________, to evaluate the gain information of each attribute.

GAIN

4- The Entropy is 1 when the collection contains number of positive examples _______ to/than negative examples.

Equal

5-The first step of FIND-S is to initialize h to the most specific hypothesis in __________: h = < Ø , Ø >

H

6- Entropy characterizes the purity/impurity of an arbitrary collection of examples.

True

7- ________ stands for interactive dichotomizer.

ID

8- If the true output of a concept [c(xi)] is 1 or 0 for an instance, then the output by our hypothesis [h(xi)] is 1 or 0 as well, respectively.

True

9-Aggregation only occurs once for each output variable, just after the fifth and final step, defuzzification.

False

10- __________ is the process by which the fuzzy sets that represent the outputs of each rule are combined into a single fuzzy set.

Aggregation

Quiz-4

1- Fuzzy inference systems are not associated with number of names:

a. True
b. False

2- A single layer perceptron can not perform pattern classification on linearly separable patterns

a. True
b. False

3- Hypothesis space uses the ___________________of the attributes

Conjunction(AND)
Disjunction(OR)
Negation(NOR)
None of given

4- Machine learning is prerequisite for any mature program of artificial intelligence

a. True
b. False

5- ____is process of formulation the mapping from given input to output using fuzzy logic

FIZ
FIS
FOS
None of given

6- Many machine learning systems are classifiers

True
False

7- The brain is collection of about 100 ____ interconnected neurons

Million
Billion
Trillion
None of given

Quiz -5

Question # 2 of 10 ( Start time: 05:56:51 PM ) Total Marks: 1

In Fuzzy Inputs we resolve all fuzzy statements in the antecedent to a degree of membership between 0 and _____

Select correct option:

a. 1
b. 2
c. 0
d. None

Question # 3 of 10 ( Start time: 05:58:07 PM ) Total Marks: 1

The tractable problems are further divided into structured and ________ problems

Select correct option:

a. Complex

Question # 4 of 10 ( Start time: 05:59:02 PM ) Total Marks: 1

The role of tester is often called the critic

Select correct option:

b. True

Question # 5 of 10 ( Start time: 06:00:07 PM ) Total Marks: 1

Which one is NOT the phase of machine learning:

Select correct option:

c. validation
d. training
e. application
f. none of given

Question # 6 of 10 ( Start time: 06:01:05 PM ) Total Marks: 1

The Candidate-Elimination algorithm represents the ____________

Select correct option:

a. version space

Question # 7 of 10 ( Start time: 06:02:36 PM ) Total Marks: 1

Mamdani’s method was among the first _____________ built using fuzzy set theory.

Select correct option:

b. control systems

Question # 10 of 10 ( Start time: 06:03:42 PM ) Total Marks: 1

_____________ learning works on existing facts and knowledge and deduces new knowledge from the old.

Select correct option:

c. deductive

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M
moaaz
Cyberian's Gold

  1. If the true output of a concept [c(xi)] is 1 or 0 for an instance, then the output by our hypothesis [h(xi)] is 1 or 0 as well, respectively.
    A. True
    B. False

  2. Decision trees give us dis-junctions of conjunctions, that is, they have the form: (A AND B) _______ (C AND D).
    A. OR
    B. AND
    C. XOR
    D. None of the given

  3. Hypothesis space uses the ________________ of the attributes.
    A. Conjunctions (AND)
    B. Disjunctions (OR)
    C. Negation (NOR)
    D. None of the given

  4. Measure of the effectiveness of an attribute in classifying the training data is called.
    A. Information Gain
    B. Measure Gain
    C. Information Goal
    D. None of the given

  5. Which one is NOT the advantage of Neural Network
    A. Excellent for pattern recognition
    B. Excellent classifiers
    C. Handles noisy data well
    D. None of the given

  6. The first step of FIND-S is to initialize h to the most specific hypothesis in __________: h = < Ø , Ø >
    A. H
    B. I
    C. J
    D. K

  7. A drawback of FIND-S is that, it assumes the consistency within the training set.
    A. True
    B. False

  8. In all calculations involving Entropy we define _________ to be ______
    A. 0 log 0, 0
    B. 0 log 10, 1
    C. 0 log 0, 1
    D. 1 log 1, 1

  9. The soma and the enclosed nucleus in neuron play a significant role in the processing of incoming and outgoing data.
    A. True
    B. False

  10. A concept is the representation of the __________ with respect to the given attributes.
    A. Solution
    B. Problem
    C. Knowledge
    D. None of the given

0
M
moaaz
Cyberian's Gold

Inductive learning takes examples and generalizes rather than starting with __________ knowledge.

Existing
Inductive
Deductive
None of the given

9dde9e93-60aa-40e5-9437-9726c52a8178-image.png

0
M
moaaz
Cyberian's Gold

In theoretical computer science there are two main branches of problems:

Select correct option:
Tractable and Intractable
Intractable and Induction
Tractable and Induction
None of the given

9a41b8cd-c0a4-4fc0-9f7d-5cb8d92ef956-image.png

0
M
moaaz
Cyberian's Gold

Which one is NOT the phase of machine learning:

Select correct option:

a. Validation
b. Training
c. Application
d. none of given

0f2572e8-d665-4070-9d51-789d83dd1ae0-image.png

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