CSCI 3302讲解、辅导Python程序语言、讲解K-Means、Python设计辅导
辅导留学生Prolog|讲解留学生Process
CSCI 3302: Introduction to Robotics
Homework 3+4: Clustering and Classification
Due Date: Dec 4, 2018 @ 11:55pm
(Extra credit available: 2pts per day early, up to a maximum of 14pts)
Using Homework3.py as a base, implement the functionality required for K-Means
clustering (50%) and K-Nearest Neighbor classification (50%). You may use numpy
or any math library you prefer, though this is not necessary. You are not permitted
to call k-Means or k-NN classifiers from other packages to implement your own.
The provided Python file will output your k-Means cluster centers and assess your
kNN classifier accuracy using Leave-One-Out-Cross Validation. You are to complete
this assignment on your own (without collaboration).
Submit your fully implemented Homework3.py file, as well as the
hw3_kmeans_*.pkl file containing your cluster centers to Moodle for full credit.