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COMP3270 Artificial Intelligence

 THE UNIVERSITY OF HONG KONG

Department of Computer Science
COMP3270 Artificial Intelligence
Assignment 3
1. Write a python program using sci-kit learn (aka sklearn) package to build a
decision tree for the mushroom dataset from the UCI Machine Learning Repository.
Split the dataset into 75% training and 25% test set. Write down the accuracy for
the test set.
2. Use Naive Bayes and Support Vector Machine to perform classification on a face
database, the Labeled Faces in the Wild (LFW ). The database can be download
from:
http://vis-www.cs.umass.edu/lfw/lfw-funneled.tgz (233MB)
Sample code is available from
https://scikit-learn.org/stable/auto examples/applications/
plot face recognition.html
Study the sample code. Try to extract eigenfaces (PCA on the images), perform
classification and report results using
(a) Naive Bayes Classifier
(b) Support Vector Machine (SVM ) using radial basis function (rbf ) kernel
Remove unnecessary code from the sample.
3. Use the same dataset (LFW ) as in Q2.
Apply a pretrained convolutional neural network, (using VGG16 ), and replace
the fully-connected layers with your own. Freeze the weights of the convolutional
layers and only train the new FC layer.
Sample code for using pre-trained VGG16 for another classification task is available
from:
 
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