CSI 5810 (Assignment # 2)
1. The folder “CSI5810TextFiles” posted on Moodle contains 8 text files. You are
to apply text-processing steps including stop word filtering to obtain termdocument matrix under Boolean Model. Using this matrix, calculate
similarity between all document pairs and show your results in the form of
an 8x8 matrix. Use Jaccard’s similarity measure.
2. This is a continuation of Exercise #1. In this case, determine the vector space
representation for each document and calculate the 8x8 document similarity
matrix using Cosine measure of similarity.
3. In this exercise, you will use “Wheat Data” posted at Moodle. The data
consists of 32 training examples each from three classes. Using these training
examples, you will perform classification of 3 test examples by k-NN
classification (k= 1, 3, and 5), weighted k-NN (3 and 5) and by Naïve Bayes
classifier. You will write your own code to implement Naive Bayes. Compare
and comment on your results.
4. In this exercise, you will again use 32 training examples of wheat data and
project them into two-dimensions using the Fisher’s LDA method for
multiple classes. Next, you will apply PCA on the same 32 examples to reduce
the data to two dimensions. You will show your result by creating two scatter
plots, one for LDA and the other for PCA. Make sure to color code the project
points with their respective class labels.