how can I identify the features of my data x that mostly contribute to the classification of linear discriminant analysis?
2 views (last 30 days)
Dear all, I would like to know whether it is possible to know what features of a data set mostly contribute to the classification performed by linear discriminant analyses.
To make my question clearer, let’s take the example available in Matlab: the Fisher’s iris data.
Each row of the data set fisheriris contains a sample of an iris flower and the columns a value for: Sepal length, Sepal width, Petal length, Petal width.
I would like to know which feature (Sepal length or width or petal length) the most contribute in the classification of one sample of iris as setosa or virginica.
Can I obtain this information using classify or fitcdiscr?
I hope that my question is clear,
Thank you for your help,
Bernhard Suhm on 13 Dec 2017
The coefficient magnitude is a measure of predictor importance. After the training with normalized data (zero mean and unit variance), this measure is stored in the DeltaPredictor property. See also answer from 3 years ago, https://www.mathworks.com/matlabcentral/answers/119122-how-can-we-know-the-most-imortant-predictor-in-discriminant-analysis