Task 1: Classification performance evaluation

Lesson 1: Species work evaluation
In this relatively resolution lesson, you are required to evaluate species work of five algorithms on three datasets using Weka. Load breast-cancer.arff, diabetes.arff and iris.arff datasets into Weka undivided at a span and pass each of the adown algorithms with their lapse settings. Then, collate a 10-fold cross-validation species results restraint redundant evaluation.

a. MultilayerPerceptron
b. Naive Bayes
c. J48
d. RandomForest
e. RERTree

You demand to transcribe a reverberation that shows work similitude of these algorithms on the datasets. The reverberation should hold redundant similitude of species ratification in conditions of the laziness matrix and other work metrics used in Weka. Include compulsory screenshots, tables, graphs, awe. to perform your reverberation pregnant, and revealing insightful details on the work similitude.