how can I identify the features of my data x that mostly contribute to the classification of linear discriminant analysis?
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Sand
el 8 de Nov. de 2017
Respondida: Bernhard Suhm
el 13 de Dic. de 2017
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,
Andrea
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Krishna Bindumadhavan
el 22 de Nov. de 2017
What is the measure (mathematically speaking) of what feature contributes the most here according to you? If you would like to visualize the effect of various features , you could look at this example here: https://www.mathworks.com/help/stats/create-and-visualize-discriminant-analysis-classifier.html .
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Bernhard Suhm
el 13 de Dic. de 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
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