Question

Computer Science
Explain the most convenient way for getting (some of) the iris data (iris data.xlsx) into the Classification
Toolbox of MatLab. (Use only the petal length and sepal length (i.e. 2 features – 2-D feature space)
and only the first 100 data points (i.e. 2 classes)). (Hints: Create variable "patterns" with iris data - may
need to transpose: “patterns" is a d-by-n matrix, where d is the number of features (=4) and n is the
number of examples (=150).Create variable "targets" with class labels: "targets” is a 1-by-N vector
containing the class labels (in this case, 0, 1 and 2).Save these as a mat file.Open Classifier, read data
(when d>2, a feature selection GUI will open and request the user to preprocess the data (e.g. by PCA)
to yield 2-D data, compatible with the display) and use appropriate classifiers (can do a Compare).)​

Answer 1

Explanation:

Computer Science

Explain the most convenient way for getting (some of) the iris data (iris data.xlsx) into the Classification

Toolbox of MatLab. (Use only the petal length and sepal length (i.e. 2 features – 2-D feature space)

and only the first 100 data points (i.e. 2 classes)). (Hints: Create variable "patterns" with iris data - may

need to transpose: “patterns" is a d-by-n matrix, where d is the number of features (=4) and n is the

number of examples (=150).Create variable "targets" with class labels: "targets” is a 1-by-N vector

containing the class labels (in this case, 0, 1 and 2).Save these as a mat file.Open Classifier, read data

(when d>2, a feature selection GUI will open and request the user to preprocess the data (e.g. by PCA)

to yield 2-D data, compatible with the display) and use appropriate classifiers (can do a Compare).)