Task 1: Classification performance evaluation

Job 1: Group work evaluation
In this proportionately dissection job, you are required to evaluate group work of five algorithms on three datasets using Weka. Load breast-cancer.arff, diabetes.arff and iris.arff datasets into Weka undivided at a duration and leak each of the under algorithms with their lapse settings. Then, sum a 10-fold cross-validation group results control leading evaluation.

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

You want to transcribe a announce that shows work similarity of these algorithms on the datasets. The announce should comprehend leading similarity of group achievement in provisions of the laziness matrix and other work metrics used in Weka. Include needful screenshots, tables, graphs, awe. to effect your announce all, and revealing insightful details on the work similarity.