![matlab average matlab average](https://i.ytimg.com/vi/WlCOYHHv9bo/maxresdefault.jpg)
If I randomly change the order of the training samples, I get the same classification accuracy but a very different meanAP. the problem thanks to your upper link, now i understand the logic for the moving average.
#MATLAB AVERAGE CODE#
However with this code I get some strange results. And then I average the results over all classes. Therefore, I want to calculate the weekly average of the measurement from the date time reference matrix (1744). This function uses the vl_pr function from vlfeat to compute the average precision for a single class. % then get the probability for that class % get the "true class" to be 1 for that class and -1 for everthing else For example, if A is a matrix, then mean(A,1 2) is the mean of all elements in A, since every element of a matrix is contained in the array slice defined by dimensions 1 and 2. tsmean mean( ts, Name,Value ) specifies additional options when computing. function meanAP = computeMeanAP(prob,allTrueClass) M mean(A,vecdim) computes the mean based on the dimensions specified in the vector vecdim. tsmean mean( ts ) returns the mean of the data samples in a timeseries object. The inputs are prob, which is the same prob_estimates from liblinear and allTrueClass which is the true class of the testing samples. Given this I wrote a short function to compute the meanAP.
![matlab average matlab average](https://www.mathworks.com/help/matlab/ref/movmean_windowing_k.png)
The prob_estimates matrix has each row being a separate sample, and each column being the score of it matching that class. I am using liblinear for classification and I am trying to use vlfeat for the precision because it already includes a built-in function to compute precision.įrom liblinear I run the command = predict(testing_label_vector, testing_instance_matrix, model) This MATLAB function returns an array of local k-point mean values, where each mean is calculated over a sliding window of length k across neighboring. I want to find the mean average precision (meanAP) from a classification problem.