1. Ray LaBarge ECE 539 Project

2.  Wild Mushrooms are available throughout North America  No “Leaves of 3, Leave it Be” rule to classify by  Consequences of misclassification are deadly!!!

3.  Dataset from UC-Irvine Machine Learning Database  Most notable work by Prof. Włodzisław Duch of Poland’s Nicolaus Copernicus University  Established 3 classifying rules with 100% accuracy odor  R 1 : odor ∈ {a,l,n}→ class e odorspore-print-colorpopulationhabitat  R 2 : odor ∈ {a,l,n} & spore-print-color ∈ {r,w} & population = v & habitat ∈ {l,p}→class e odorspore-print-colorpopulationgill-size  R 3 : odor ∈ {a,l,n} & spore-print-color ∈ {r,w} & population = v & gill-size = b →class e  R 4 : ELSE→ class p

4.  Develop k-NN Algorithm  Determine baseline performance  Establish if any relation between physical characteristics and toxicity exists  Develop a Perceptron  Randomize data and partition into Train and Test  Use 3 way cross validation  All algorithms implemented in Java

5. 99.90% 99.90% accurate averaged from a 3-way cross validation

6. Percentages are averaged over 3 cross validations of data More than 99% accuracy!

7. Note: Using learning rates of 0.01 and 0.001 had the same testing set accuracy. More than 99% accuracy!

8. MOST LIKELY POISONOUS IF...MOST LIKELY EDIBLE IF…