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Ch. 1- 4 Data Mining_ Practical Machine Learning Tools and Techniques.
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Ch. 1- 4 Data Mining_ Practical Machine Learning Tools and Techniques.
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Ch. 1- 4 Data Mining: Practical MachineLearning Tools and Techniques
Finding the telephone number of your friend from a phone directory is a data
mining activity
True
False - correct answer-False
Signatures in data that can be examined, reasoned about, and used to inform
future decisions are called ________________
a. Decision list
b. Structural patterns
c. Learning method
d. Hidden patterns - correct answer-b. Structural patterns
Using the WEKA package, load the data set contained in the file
weather.nominal.arff . This data set has __________ attributes - correct
answer-5 attributes
The attribute outlook in the weather data is of type:
a. Nominal
b. Ordinal
c. Interval
d. Ratio - correct answer-a. Nominal
The attribute temperature in the weather data is of type:
a. Nominal
b. Ordinal
c. Interval
d. Ratio - correct answer-a. Nominal
Build a decision tree using the weather data using 10 fold cross-validation.
The confidence factor used building the decision tree is: ________ - correct
answer-0.25
, Number of leaves in the tree is: __________ - correct answer-5
From the confusion matrix the number of "yes" classes that has been
misclassified is: _____________ - correct answer-4
When outlook is sunny and humidity is high then play is no. How many
examples are classified as no? - correct answer-3
For what value of the outlook attribute are all examples always classified as
yes?
a. sunny
b. rainy
c. overcast - correct answer-c. overcast
The zero-R method classifies data:
a. By selecting the best attributes to define rules
b. By assigning the new data to the majority class
c. By using Bayes rule
d. All of the above - correct answer-b. By assigning the new data to the
majority class
Most sophisticated models are the best classifiers:
True
False - correct answer-False
The 1R classifier, classifies data by:
a. Using all the attributes in the data
b. By testing a single attribute
c. By using a combination of attributes
d. None of the above - correct answer-b. By testing a single attribute
Missing values and numeric values cannot be handled by 1R:
True
False - correct answer-False
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