Created
February 10, 2019 15:36
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| newDataset = sio.loadmat('anomalyDataTest.mat') | |
| Xtest = newDataset['X'] | |
| Xvaltest = newDataset['Xval'] | |
| yvaltest = newDataset['yval'] |
I think I have mentioned how to extract the outliers at the last. Please find it there in the blog :)
I did not understand the rest of your question about yval.
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How can we get the yval array.
Do I have to manually look into the validation data and discover the indices which has outlier, or is there any other way?
Also how to make this yval if we have multidimensional array, i.e. more than 1 feature