what value of k in KNN method will give the best accuracy for leave-one-out crossvalidation.

For the above figure, what value of k in KNN method will give the best accuracy for leave-one-out crossvalidation. Report accuracy and k value. (3 marks) 2. In classification, overfitting and underfitting is a big problem. Does it happen in Random Forest or not? Why? (3 marks) Part-2: (24 marks = 4 methods x 6): Using the following four supervised machine learning methods, answer questions(A-D). 1. Support Vector Machine 2. K-Nearest Neighbour 3. Decision Tree, and 4. Random Forest A. Build optimised classification model to predict the chronic kidney disease from the dataset. (1 marks) B. For each optimised model, answer the followings – ? which hyperparameters were optimised? [Hint: For SVM, kernel can be considered as one of the hyperparameters.] ? what set or range of values were used for each hyperparameter? ? which metric was used to measure the performance? ? justify your design decisions. C. Plot the prediction performance against hyperparameter values to visualise the optimisation process and mark the optimal value. (1 marks) SIT720 Machine Learning Assessment Task 5: Machine Learning Project ©Deakin University 3 SIT720 D. Evaluate the model (obtained from A) performance on the test set. Report the confusion matrix, F1-score and accuracy. (1 marks) Part-3: Discussion (5 marks) Based on the results obtained in Part-2, which classification method showed the best performance and why? Do you have any suggestions to further improve the model performances? (5 marks) Submission details Deakin University has a strict standard on plagiarism as a part of Academic Integrity. To avoid any issues with plagiarism, students are strongly encouraged to run the similarity check with the Turnitin system, which is available through Unistart. A Similarity score MUST NOT exceed 39% in any case. Late submission penalty is 5% per each 24 hours from- Thursday 1 October 2020 11:30 pm (AEST). No marking on any submission after 5 days (24 hours X 5 days from- Thursday 1 October 2020 11:30 pm (AEST)). Extension requests Requests for extensions should be made to Unit/Campus Chairs well in advance of the assessment due date. If you wish to seek an extension for an assignment, you will need to submit a request using the “Extension Request” link of the “Assessment” menu in the unit site, as soon as you become aware that you will have difficulty in meeting the scheduled deadline, but at least 3 days before the due date. When you make your request, you must include appropriate documentation (medical certificate, death notice) and a copy of your draft assignment. Conditions under which an extension will normally be approved include: Medical To cover medical conditions of a serious nature, e.g. hospitalisation, serious injury or chronic illness. Note: Temporary minor ailments such as headaches, colds and minor gastric upsets are not serious medical conditions and are unlikely to be accepted. However, serious cases of these may be considered. Compassionate e.g. death of close family member, significant family and relationship problems. Hardship/Trauma e.g. sudden loss or gain of employment, severe disruption to domestic arrangements, victim of crime. Note: Misreading the timetable, exam anxiety or returning home will not be accepted as grounds for consideration

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