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The following table consists of training data from an employee database. The data have been generalized; for example, 3 1 . . . 3 5
The following table consists of training data from an
employee database. The data have been generalized; for example,
for age represents the age range of to The class label
is status.
Department Age Salary Status
Sales KK Senior
Sales KK Junior
Sales KK Junior
Systems KK Junior
Systems KK Senior
Systems KK Junior
Systems KK Senior
Marketing KK Junior
Marketing KK Junior
Marketing KK Senior
Sales KK Senior
Use ID algorithm, which selects attribute with highest
information gain to construct a decision tree from the given data.
Using the Naive Bayes algorithm, how would the following
examples be classified? Make sure to show your work as well as
the final classification.
a "Marketing", KK
b "Sales", KKQuestion : The follo wing table consists of training data from an
emplo yee database. The data have been generalized; for example.
dots for age represents the age range of to The class label
is status.
Use ID algorithm, which selects attribute with highest
information gain to construct a decision tree from the given data.
Using the Naive Bayes algorithm, how would the following
e xamples be classified? Make sure to show your work as well as
the final classification.
a "Marketing", KK
b "Sales", KK solve the problem and give me an answer with detailed explanation of each step
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