Task 1: Classification performance evaluation

Labor 1: Character execution evaluation
In this relatively resolution labor, you are required to evaluate character execution 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 retreat each of the beneath algorithms with their lapse settings. Then, glean a 10-fold cross-validation character results coercion redundant evaluation.

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

You insufficiency to transcribe a description that shows execution similitude of these algorithms on the datasets. The description should hold redundant similitude of character truthfulness in conditions of the laziness matrix and other execution metrics used in Weka. Include needful screenshots, tables, graphs, foreseeing. to mould your description generic, and revealing insightful details on the execution similitude.