I have built a Sequential model to predict dataset. The output is an array of values something like below:
[[25.672846 ]
[35.517834 ]
[16.25976 ]
[27.06339 ]
[15.176579 ]
[20.261982 ]
[17.346558 ]
[14.3797455]
[23.327494 ]
[17.967245 ]
[17.85637 ]
[16.672417 ]
[ 6.2621603]
[20.35404 ]]
I want to sort the array in ascending order.
I've tried
pred = np.sort(model.predict(data))
and
pred = np.argsort(model.predict(data))
and I've failed.
You should use np.sort as follows:
pred = np.sort(model.predict(data), axis=0)
Default behaviour is axis=-1 which is equivalent to axis=1 in your case.
If you want to sort the array in the number you can use the below
pred = model.predit(data)
pred.sort()
print(p)
This will show sorted preds. By default, the sort is in ascending order
if you want the index of the sorted
pred = model.predict(data)
sorted_index = pred.argsort(axis=0)
print(sorted_index)
Apply np.reshape(x, -1) before sorting. This way you will have a flat array which is something you might want to do eventually after sorting anyway. This is why I would prefer this over specifying the axis which is otherwise a good solution too.
machine-learningorKeras(tags edited).