Assignment1 Instructions 2017

Assignment1_instructions_2017

Assignment1_instructions_2017

Assignment1_instructions_2017

User Manual: Pdf

Open the PDF directly: View PDF PDF.
Page Count: 1

DownloadAssignment1 Instructions 2017
Open PDF In BrowserView PDF
Human-centered Assistive
Robotics
Technische Universität München

MACHINE LEARNING
IN ROBOTICS
Assignment1 Instructions

Prof. Dr.-Ing. Dongheui Lee

SUBMISSION
Each student must work independently. Please upload a file called Assignment1 Surname ID.zip (where
Surname is the surname of the student that submits the file and ID is the enrollment number) on moodle.
This file should contain:
• Assignment1 Surname.pdf , a pdf file containing the solution to all the exercises (see below for
further informations)
• The Matlab code in a subfolder called Code. Students can create any functions that they consider
necessary to solve the problems.
The submission deadline is on the 23.06.2017 at 23.59.
HW1 Surname.pdf .
• Students need to provide a pdf file containing the solution to all the exercises. Students must clearly
indicate in this file to which exercises and to which question the solutions refer to.
• For Exercise1.a − b) report learned parameter values as well as optimal values of p1 and p2 for
k = 2 and k = 5.
• For Exercise1.c) attach the required plots.
• For Exercise2.) report the optimal d value, its classification error and confusion matrix. Also attach
a plot of classification errors when varying d from one to sixty.
• For Exercise3.a − b) attach the resulting plots.
Subfolder Code.
• For Exercise1 provide a matlab function Exercise1.m. The input to this function is k and it’s
output is the cell array par.
• For Exercise2 provide a matlab function Exercise2.m. The input to this function should be dmax
which is 60 in this exercise. The outputs of this function should be a plot of classification errors (from
d = 1 to dmax ), optimal value of d and its classification error and the confusion matrix.
• For Exercise3 provide a matlab functions Exercise3 kmeans.m and Exercise3 nubs.m. The inputs
to Exercise3 kmeans.m are the motion data, the initial cluster label and the number of clusters.
You can’t use the matlab function “kmeans”. The inputs to Exercise3 nubs.m are the motion data
and the number of clusters. The outputs of both function are the 3 plots required in Exercise3.a−b).
NOTES
• Do not include the provided datasets in you submission.
• We will mark the assignment even if you forget to press the submit button.
Source Exif Data: 
File Type                       : PDF
File Type Extension             : pdf
MIME Type                       : application/pdf
PDF Version                     : 1.4
Linearized                      : No
Page Count                      : 1
Producer                        : pdfTeX-1.40.10
Creator                         : TeX
Create Date                     : 2017:05:24 14:57:44+02:00
Modify Date                     : 2017:05:24 14:57:44+02:00
Trapped                         : False
PTEX Fullbanner                 : This is pdfTeX, Version 3.1415926-1.40.10-2.2 (TeX Live 2009/Debian) kpathsea version 5.0.0
EXIF Metadata provided by EXIF.tools

Navigation menu