Compute the relevant pivot tables

Reference no: EM132623563

Data Science - Naive Bayes

Please divide your data-set into training set and testing set.

Please compute the relevant pivot tables (from the training-set) using google-sheet, and translate them into conditional probabilities.

Please build using a google sheet a formula that assigns a class label to a entity/record in the dataset according to the values of its features.

Please apply the formula to a set of entities/records from the testing data-set and check the accuracy of the classifier you have built.

To analyze the effect of each feature on the classifier, try different sets of features as input to the classifier and see the effect on the accuracy of the classifier.
• Explain the results of your analysis.
• Explain the final selection of features used for the classifier (6 points) Bonus: Build a process in RapidMiner to perform the same classification process and compare the results of the google-sheet classifier to the results obtained by the rapid miner. (15 points as bonus) Note: The output of Naïve Bayes classifier phase should be
• Shared the google sheet you have created (with anyone how have the link) , and include the link in the document you will create for this phase
• A word/pdf document with detailed answers to the above questions o Answers should be short and accurate o You should add screen-shots as required to explain and support your analysis

Attachment:- vgsales.rar

Reference no: EM132623563

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