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Use the IRIS dataset that comes with Weka to compare the classification performance of the following algorithms.
1. NaiveBayesSimple
2. MultiLayerPerceptron
For each classifier, run the test once using the training set for testing, and once using 5-fold cross-validation.
•Write a short report that explains your work. This report should address the following issues. ?Description of the dataset.
1. A table describing the results.
2. A discussion/explanation of the results and the algorithms' performance. Also, explain why the accuracy is higher when "use training set" is selected for testing, rather than "cross-validation".
Define the terms entity, attribute, role and relationship between the entities, giving examples for each of them. Ans: Entity: An entity is a "thing" or "object" in th
An entity type usually has an attribute whose values are distinct for every individual entity in the collection. Such an attribute is known as a key attribute and its values can be
Provide Examples of different types of Time and Date formats. It's most common store dates using a dash (-) as a colon (:)and the delimiter as the time delimiter. The given fo
Text Processing: Use readLines to read SOU.txt into R. Create a vector called Pres containing the names of the presidents giving each speech. To do this, rst identify the lin
what is correlation in nested query
Association as a cache This association must be updated when any new element is added to it, but testing for overlap using association is more efficient. Figure:
An Enterprising group of Entrepreneurs introduced a new business named StoreItRite which is based on data storage and retrieval services. It provides the services and the company c
Three way to handle missing field val
Use of partial data by applications : In common, applications work with views rather than whole relations. Thus, it may be more appropriate to work with subsets of relations rather
Question: Consider the following database relations for a textbook ordering system used by a college bookshop: Book (b-copy#, bname, ISBN#, author, price, subject) Order (s#
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