Computer-Oriented Approaches to Pattern Recognition

by William S. Meisel.

This is an enjoyable textbook first textbook in pattern recognition that is very easy to read and follow. The problems are enjoyable and interesting. I would recommend it highly. In addition, I have implemented many of the problems from Meisel's book in Matlab below.

Download Problem Solutions (Part 1 of 1).

Code For Various Problems:
    Chapter 3 (Introduction to Optimization Techniques): Chapter 4 (Linear Discriminant Functions and Extensions):
    • prob_4_3.m (search for a linear separating hyperplane with various learning rate schedules)
    • prob_4_5.m (search for a linear separating hyperplanes for a three class problem)
    • prob_4_6.m (search for a linear separating hyperplane using the many-at-a-time algorithm)
    • prob_4_7.m (search for a linear separating hyperplane using the one-at-a-time algorithm)
    Chapter 8 (Cluster Analysis and Unsupervised Learning):
    • prob_8_3.m (the Sebestyen-Edie clustering algorithm)
    • prob_8_4.m (the similarity matrix method for clustering)
    • prob_8_6.m (an example for iterative cluster adjustment)
    • Auxiliary routines developed for this chapter:
      • cluster_N_plot.m (iterative cluster adjustment)
      • mDSTLNN.m (average of the squared distance to the L-th nearest neighbor)
      • findNearestCluster.m (finds the nearest "cluster" based on the distance to each centroid the centroid normalized by the standard deviation)
    Chapter 9 (Feature Selection):
    • prob_9_3.m (project samples to minimize the ratio of the intraset (same class) distances over the interset (different class) distances)
    • prob_9_4.m (a piecewise linear transformation such that the projected samples are linearly separable ... unfinished)
    • prob_9_5.m (rank each feature using Fisher's criterion (the features mean difference over sum of their variances))
    • Auxiliary routines developed for this chapter:

John Weatherwax
Last modified: Thu Jun 29 21:15:11 EDT 2006