Using WEKA software, answer the following questions based on the Phishing dataset provided. a) Draw a simple confusion matrix (general one, not from WEKA) of the possible data scenarios for this
Phishing dataset. (0.5 Mark)
b) Draw a table that will outline the Accuracy, Precision, Recall, F-Measure, ROC Area of the following
Rules based algorithms; RIPPER (JRip), PART, and Decision Table (2 Marks)
c) Use Decision Trees algorithms (Random Forest, Random Tree) and Artificial Neural Network
(Multilayer Perceptrol) to compare with the results in part b) above. Do you have better prediction
accuracy with these in this dataset? (2 Marks)
d) What is your conclusion in these experiments pertaining to ML algorithms used? (0.5 Mark)
By

$527.7.if the following was the question  $527.7 is the answer.students who are trying to raise funds have an agreement with a local pizza chain. the chain has agreed to sell them pizzas at a discount, which the students can then resell to families in the local community for a profit. it is expected that of the 500 families in the community, at most 70% will buy pizza. based on a survey of their personal preferences, the students believe that they should order no more than 120 cheese pizzas, no more than 150 pepperoni pizzas, and no more than 100 vegetarian pizzas. they also want to make sure that at least 20% of the total pizzas are cheese and at least 50% of the pizzas are pepperoni. they make a profit of $1.45, $1.75, and $1.98, respectively, for each cheese, pepperoni, and vegetarian pizza they resell. how many pizzas of each type should they buy?

What's the rest of the problem? lol