how can I constrain weights of linear classifier in MATLAB?

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Heeseung Lee
Heeseung Lee 2015 年 12 月 23 日
回答済み: Rakesh Chavan 2016 年 1 月 4 日
I am graduate student studying system neuroscience in Korea. I have a problem and need your help... problem is like below.
There are a number of neurons and we know their firing rates on -3s, -2s, -1s, like
neuron index :
1 2 3 4
firing rata
0s: 1 1 -1 1
-1s: -1 -1 0 -1
-2s: 0 0 0 0
-3s: 1 1 1 1
By using these fire rate history, I want to predict current(0s) firing rate of neurons whether it is 1 or -1. I am using linear SVM and varying weights of each time point. But, I want to constrain absolute value of weight of recent firing rate is always larger than that of past like
weight of
-1s: -0.8
-2s: 0.3
-3s: -0.1
How can I realize this idea on linear classifier like linear SVM on MATLAB? (of course, other linear classifier would be welcomed)
please help me...

回答 (1 件)

Rakesh Chavan
Rakesh Chavan 2016 年 1 月 4 日
It is possible to create a linear SVM model using the 'fitcsvm' function based on the training data.
You can use the 'predict' function to for classifying new data using a trained SVM classifier:
A general overview of the process is given in the following link:
For generating a linear discriminant analysis classifier the 'fitcdiscr' can be used. The weights option for this function can be used to specify custom weights. Kindly refer to the following link:


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