# Help With ECE 403/503 Ghostwriter Matlab Programming

LABORATORY MANUAL
ECE 403/503
OPTIMIZATION for MACHINE LEARNING

This manual was prepared by
Wu-Sheng Lu

University of Victoria
Department of Electrical and Computer Engineering

May 2020
2

The objective of the experiments described in this manual is to familiarize the student
with computer simulations and implementation of several optimization as well as data
processing techniques as they are applied to machine learning problems. The primary
software tool required in all experiments is MATLAB to which the student can access
during the laboratory sessions. An appendix, that introduces main functions in MATLAB
and their usage, is included to facilitate the students in preparing their MATLAB code.

PREPARATION

Successful completion of an experiment depends critically on error-free MATLAB
programming. Therefore, preparation prior to the laboratory period is essential.
Specifically, the student should study the description of the experiment and prepare
useable MATLAB codes required in the preparation section(s) before the experiment is
carried out. The student will be required to present the preparation at the beginning of the
lab session.

THE LABORATORY REPORT

A laboratory report is required from each group for each experiment performed. The lab
report should be submitted within one week after the experiment. The front page of the
report is shown on the next page and should be used for each laboratory report.

The report should be divided into the following parts:
(a) Objectives.
(b) Introduction.
(c) Results including relevant MATLAB programs and figures, and description of the
implementations.
(d) Discussion.
(e) Conclusions.
where {( , ), 1, 2,...,314}p py p x used in (E1.5) are from train data {Xh_tr,y_tr},
while {( , ), 1, 2,...,78}t ty t x used in (E1.6) are from test data {Xh_te,y_te}, both
were prepared in Sec. 2.3. Report your numerical results in terms of RMSEtrain and
RMSEtest.
3.6 For comparison, in a single figure, plot the “ground truth” output y_te as a curve
colored in blue and its prediction ˆ ˆ{ , 1,2,...,78}T t t
 w x as the second curve colored
in red. Comment on your visual inspection of the figure.

Include your MATLAB code in the lab report.