|Homework #6 Due: Tuesday, 11/21/20|
1. Implement a fuzzy pattern classifier for digits 0-9.
– The digits are patterns on a 29×29 bitmap. The digits are normalized to 27×27 size.
– Follow the example from the class notes to convert the binary bitmap in to a fuzzy feature set.
– Use the supplied training data.
– Use genetic algorithms to produce a fuzzy classifier which is using only fuzzy operators AND and NOT (similar to the class example, but not using OR).
– For each classifier map the features on a color-coded (and numbered) graph and supply this graph in your report. (For example, if a square is included into the classification formula directly, color it blue. If a square is included into the classification formula with NOT, color it red. If a square is not included into the classification formula, color it white.)
– The final classifier program must take a file in the format of the training set as the input, show the scores for all digits from 0 to 9, and show the recognized digit.
Materials and hints:– The training data and Matlab functions to access them are supplied here.- Run readme.m to look at all training patterns.
– Depending on how you have implemented the fuzzify() function in the fuzzy toolbox, you may want to reuse it for computing fuzzy features.
– Train a single digit classifier at a time.
– A suggestion for the fitness function: a classifier will have maximum fitness when it recognizes all correct patterns in the training set with a score of 1, and scores all other patterns in the training set with a score of 0. (Example: all paterns for digit 3 are recognized as 3 with a score of 1.0, while patterns for digits 0-2,4-9 are scored as 0.0)
– Follow the in-class discussion on the specifics of implementation.
60 pts. The classifier correctly classifies all patterns from the training set.
10 pts. Report satisfying all requirements listed in the syllabus and this assignment.
3 pts max. For correct classification of each of the 10 test patterns to be presented to the classifier.
If a pattern cannot be recognized by anyone’s classifier, it will be replacedIf a pattern can be recognized only by a single person’s classifier, that person scores +3pts. everybody else scores +1pts.If a pattern can be recognized by two classifiers only, those persons score +3pts, everybody else scores +0.5pts.If a pattern can be recognized by three or more classifiers, those persons score +3pts, everybody else scores 0pts.