منتدى طلاب وطالبات الجامعة السعودية الإلكترونية لا تنسوا IT446-Online Quiz 2
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منذ /21-04-2018, 09:34 PM   #1

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 رقم العضوية : 10456 تاريخ الإنتساب : Jul 2014 مقر الإقامة : جدة فرع الجامعة : فرع جدة التخصص : بكالوريوس تقنية معلومات المستوى : المستوى الثامن المشاركات : 136 الجنس : ذكر مستوى التقييم : النقاط : 22

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تم شكره 6 مرة في 4 مشاركة
لا تنسوا IT446-Online Quiz 2

QUESTION 1

The minimum eccentricity of all vertices is called

a.
Eccentricity

b.

c.
Diameter

d.
Peripheral Vertex

0.1 points

QUESTION 2

____________ is a density-based clustering Method.

a.
DBSCAN

b.
OPTICS

c.
DENCLUE

d.
All the above

0.1 points

QUESTION 3

Clustering is an approach that uses which learning technique:

a.
By Observation

b.
By examples

c.
By listening

d.
All of above

0.1 points

QUESTION 4

Less time in training but more time in predicting

a.
Lazy Learning

b.
Eager Learning

c.
a and b

d.
None of the above

0.1 points

QUESTION 5

In holdout method, the given data is randomly partitioned into _____ independent sets.

a.
one

b.
two

c.
many

d.
none of the above

0.1 points

QUESTION 6

_________________ is a two steps process model that describes and distinguishes data classes or concepts.

a.
Data selection

b.
Data Characterization

c.
Data Classification

d.
Data discrimination

0.1 points

QUESTION 7

In ___________ each cluster is represented by one of the objects of the cluster located near the center.

a.
k-medoid

b.
k-means

c.
STIRR

d.
ROCK

0.1 points

QUESTION 8

If an object has deviated significantly from the data set based on certain conditions such as time or location, it is considered which type of outlier?

a.
Contextual Outlier

b.
Global Outlier

c.
Collective Outlier

d.
Not an outlier

0.1 points

QUESTION 9

A ________________ is a tree like diagram that graphically displays hierarchical clustering

a.
dendrogram

b.
decision tree

c.
histogram

d.
None of the above

0.1 points

QUESTION 10

Hierarchical clustering methods

a.
Are always top-down in their approach to forming hierarchies

b.
Are impervious to the choice of split / merge points

c.
Start either with individual objects as clusters or with the entire data set as a single cluster

d.
All of the above

0.1 points

QUESTION 11

Bayesian belief networks (BBN) differ from naïve Bayesian classifiers (BC) in that :

a.
BBNs are always more computationally more efficient than are BCs

b.
BCs assume the values of the attributes in a tuple are conditionally independent, while BBNs do not make that assumption

c.
BCs are always more accurate, even when the data tuples have attribute values that are not necessarily conditionally independent

d.
No significant differences exist

0.1 points

QUESTION 12

____________ is called structural-context similarity.

a.
In-Neighborhood

b.
out-neighborhood

c.
SimRank

d.
Distance

0.1 points

QUESTION 13

ROC stands for

a.
Return Operation Curve

b.

c.
Rapid Operating Curve

d.

0.1 points

QUESTION 14

K-mean is a

a.
Method for creating clusters based on similarities amongst members of a cluster

b.
Method for clustering that requires an initial value, k, that predetermines the number of clusters to create from a given data set

c.
Both a and b

d.
None of the above

0.1 points

QUESTION 15

Which one of the following is the major category of clustering methods for high-dimensional data

a.
Statistical methods

b.
Dimensionality reduction methods

c.
Bagging

d.
Normalization

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