MEProject:
Project:
In the data below, we have four numeric attributions for three classes of iris flowers as follows:
Attribute Information:
1. sepal length in cm
2. sepal width in cm
3. petal length in cm
4. petal width in cm
5. class:
-- Iris Setosa
-- Iris Versicolou
-- Iris Virginica
There are 50 measurements for each, so that the total number of data is 150 rows. Split the
data into two parts: training data and testing data.
Develop and test different classification methods:
a- Bayesian likelihood ratio,
- discriminant functions based on Gaussian modeling, ie. fit the data to Gaussian distributions
and find the
mean and variance or covariance matrices using MLE; maximum likelihood estimation.
c- classification based on Parzen windows
d- classification based on kNN, use different k, and different distance measures.
e- what is the rate of success (in percent) for each approach?
Part a and b, will be due in 10 days. Please study the project and let me know by email or in
class if you have any questions on how to approach each part.
Thanks
Datasets:
5.1,3.5,1.4,0.2,Iris-setosa
4.9,3.0,1.4,0.2,Iris-setosa
4.7,3.2,1.3,0.2,Iris-setosa
4.6,3.1,1.5,0.2,Iris-setosa
5.0,3.6,1.4,0.2,Iris-setosa
5.4,3.9,1.7,0.4,Iris-setosa
4.6,3.4,1.4,0.3,Iris-setosa
5.0,3.4,1.5,0.2,Iris-setosa
4.4,2.9,1.4,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
5.4,3.7,1.5,0.2,Iris-setosa
4.8,3.4,1.6,0.2,Iris-setosa
4.8,3.0,1.4,0.1,Iris-setosa
4.3,3.0,1.1,0.1,Iris-setosa
5.8,4.0,1.2,0.2,Iris-setosa
5.7,4.4,1.5,0.4,Iris-setosa
5.4,3.9,1.3,0.4,Iris-setosa
5.1,3.5,1.4,0.3,Iris-setosa
5.7,3.8,1.7,0.3,Iris-setosa
5.1,3.8,1.5,0.3,Iris-setosa
5.4,3.4,1.7,0.2,Iris-setosa
5.1,3.7,1.5,0.4,Iris-setosa
4.6,3.6,1.0,0.2,Iris-setosa
5.1,3.3,1.7,0.5,Iris-setosa
4.8,3.4,1.9,0.2,Iris-setosa
5.0,3.0,1.6,0.2,Iris-setosa
5.0,3.4,1.6,0.4,Iris-setosa
5.2,3.5,1.5,0.2,Iris-setosa
5.2,3.4,1.4,0.2,Iris-setosa
4.7,3.2,1.6,0.2,Iris-setosa
4.8,3.1,1.6,0.2,Iris-setosa
5.4,3.4,1.5,0.4,Iris-setosa
5.2,4.1,1.5,0.1,Iris-setosa
5.5,4.2,1.4,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
5.0,3.2,1.2,0.2,Iris-setosa
5.5,3.5,1.3,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
4.4,3.0,1.3,0.2,Iris-setosa
5.1,3.4,1.5,0.2,Iris-setosa
5.0,3.5,1.3,0.3,Iris-setosa
4.5,2.3,1.3,0.3,Iris-setosa
4.4,3.2,1.3,0.2,Iris-setosa
5.0,3.5,1.6,0.6,Iris-setosa
5.1,3.8,1.9,0.4,Iris-setosa
4.8,3.0,1.4,0.3,Iris-setosa
5.1,3.8,1.6,0.2,Iris-setosa
4.6,3.2,1.4,0.2,Iris-setosa
5.3,3.7,1.5,0.2,Iris-setosa
5.0,3.3,1.4,0.2,Iris-setosa
7.0,3.2,4.7,1.4,Iris-versicolo
6.4,3.2,4.5,1.5,Iris-versicolo
6.9,3.1,4.9,1.5,Iris-versicolo
5.5,2.3,4.0,1.3,Iris-versicolo
6.5,2.8,4.6,1.5,Iris-versicolo
5.7,2.8,4.5,1.3,Iris-versicolo
6.3,3.3,4.7,1.6,Iris-versicolo
4.9,2.4,3.3,1.0,Iris-versicolo
6.6,2.9,4.6,1.3,Iris-versicolo
5.2,2.7,3.9,1.4,Iris-versicolo
5.0,2.0,3.5,1.0,Iris-versicolo
5.9,3.0,4.2,1.5,Iris-versicolo
6.0,2.2,4.0,1.0,Iris-versicolo
6.1,2.9,4.7,1.4,Iris-versicolo
5.6,2.9,3.6,1.3,Iris-versicolo
6.7,3.1,4.4,1.4,Iris-versicolo
5.6,3.0,4.5,1.5,Iris-versicolo
5.8,2.7,4.1,1.0,Iris-versicolo
6.2,2.2,4.5,1.5,Iris-versicolo
5.6,2.5,3.9,1.1,Iris-versicolo
5.9,3.2,4.8,1.8,Iris-versicolo
6.1,2.8,4.0,1.3,Iris-versicolo
6.3,2.5,4.9,1.5,Iris-versicolo
6.1,2.8,4.7,1.2,Iris-versicolo
6.4,2.9,4.3,1.3,Iris-versicolo
6.6,3.0,4.4,1.4,Iris-versicolo
6.8,2.8,4.8,1.4,Iris-versicolo
6.7,3.0,5.0,1.7,Iris-versicolo
6.0,2.9,4.5,1.5,Iris-versicolo
5.7,2.6,3.5,1.0,Iris-versicolo
5.5,2.4,3.8,1.1,Iris-versicolo
5.5,2.4,3.7,1.0,Iris-versicolo
5.8,2.7,3.9,1.2,Iris-versicolo
6.0,2.7,5.1,1.6,Iris-versicolo
5.4,3.0,4.5,1.5,Iris-versicolo
6.0,3.4,4.5,1.6,Iris-versicolo
6.7,3.1,4.7,1.5,Iris-versicolo
6.3,2.3,4.4,1.3,Iris-versicolo
5.6,3.0,4.1,1.3,Iris-versicolo
5.5,2.5,4.0,1.3,Iris-versicolo
5.5,2.6,4.4,1.2,Iris-versicolo
6.1,3.0,4.6,1.4,Iris-versicolo
5.8,2.6,4.0,1.2,Iris-versicolo
5.0,2.3,3.3,1.0,Iris-versicolo
5.6,2.7,4.2,1.3,Iris-versicolo
5.7,3.0,4.2,1.2,Iris-versicolo
5.7,2.9,4.2,1.3,Iris-versicolo
6.2,2.9,4.3,1.3,Iris-versicolo
5.1,2.5,3.0,1.1,Iris-versicolo
5.7,2.8,4.1,1.3,Iris-versicolo
6.3,3.3,6.0,2.5,Iris-virginica
5.8,2.7,5.1,1.9,Iris-virginica
7.1,3.0,5.9,2.1,Iris-virginica
6.3,2.9,5.6,1.8,Iris-virginica
6.5,3.0,5.8,2.2,Iris-virginica
7.6,3.0,6.6,2.1,Iris-virginica
4.9,2.5,4.5,1.7,Iris-virginica
7.3,2.9,6.3,1.8,Iris-virginica
6.7,2.5,5.8,1.8,Iris-virginica
7.2,3.6,6.1,2.5,Iris-virginica
6.5,3.2,5.1,2.0,Iris-virginica
6.4,2.7,5.3,1.9,Iris-virginica
6.8,3.0,5.5,2.1,Iris-virginica
5.7,2.5,5.0,2.0,Iris-virginica
5.8,2.8,5.1,2.4,Iris-virginica
6.4,3.2,5.3,2.3,Iris-virginica
6.5,3.0,5.5,1.8,Iris-virginica
7.7,3.8,6.7,2.2,Iris-virginica
7.7,2.6,6.9,2.3,Iris-virginica
6.0,2.2,5.0,1.5,Iris-virginica
6.9,3.2,5.7,2.3,Iris-virginica
5.6,2.8,4.9,2.0,Iris-virginica
7.7,2.8,6.7,2.0,Iris-virginica
6.3,2.7,4.9,1.8,Iris-virginica
6.7,3.3,5.7,2.1,Iris-virginica
7.2,3.2,6.0,1.8,Iris-virginica
6.2,2.8,4.8,1.8,Iris-virginica
6.1,3.0,4.9,1.8,Iris-virginica
6.4,2.8,5.6,2.1,Iris-virginica
7.2,3.0,5.8,1.6,Iris-virginica
7.4,2.8,6.1,1.9,Iris-virginica
7.9,3.8,6.4,2.0,Iris-virginica
6.4,2.8,5.6,2.2,Iris-virginica
6.3,2.8,5.1,1.5,Iris-virginica
6.1,2.6,5.6,1.4,Iris-virginica
7.7,3.0,6.1,2.3,Iris-virginica
6.3,3.4,5.6,2.4,Iris-virginica
6.4,3.1,5.5,1.8,Iris-virginica
6.0,3.0,4.8,1.8,Iris-virginica
6.9,3.1,5.4,2.1,Iris-virginica
6.7,3.1,5.6,2.4,Iris-virginica
6.9,3.1,5.1,2.3,Iris-virginica
5.8,2.7,5.1,1.9,Iris-virginica
6.8,3.2,5.9,2.3,Iris-virginica
6.7,3.3,5.7,2.5,Iris-virginica
6.7,3.0,5.2,2.3,Iris-virginica
6.3,2.5,5.0,1.9,Iris-virginica
6.5,3.0,5.2,2.0,Iris-virginica
6.2,3.4,5.4,2.3,Iris-virginica
5.9,3.0,5.1,1.8,Iris-virginica