<p>I am trying to sort the instances within each of 5 classification categories in a dataset that has been put through both a random forest classifier and a neural network with 99% accuracy on each.</p>
<p>Essentially what I am trying to do is stack a sorting algorithm on top of a random forest or a neural net (depending on which will boast a much more efficient and swift process in being integrated with a sorting algorithm post-output) so that the correctly classified instances within each category can be sorted into separate organized and easily comprehensible lists.</p>
<p>I have tried researching this but all I have found are examples of ensemble learning and traditional stacking in order to achieve higher overall accuracy on an algorithm.</p>
<p>I am trying to see how I can take the correct predictions from either of these algorithms and sort them by some arbitrary features that I will engineer, but all I am wondering at the moment is how to integrate a sorting algorithm in the first place into the output of a classification algorithm.</p>

<neural-networks><machine-learning><classification><ensemble-learning><random-forests>
How do I take the correct classification predictions of an ml algo (i.e. random forest/neural net) and sort the instances in each category?
Rocko
# How do I take the correct classification predictions of an ml algo (i.e. random forest/neural net) and sort the instances in each category?

(Asked by: username_0 on 2021-04-22)

I am trying to sort the instances within each of 5 classification categories in a dataset that has been put through both a random forest classifier and a neural network with 99% accuracy on each.

Essentially what I am trying to do is stack a sorting algorithm on top of a random forest or a neural net (depending on which will boast a much more efficient and swift process in being integrated with a sorting algorithm post-output) so that the correctly classified instances within each category can be sorted into separate organized and easily comprehensible lists.

I have tried researching this but all I have found are examples of ensemble learning and traditional stacking in order to achieve higher overall accuracy on an algorithm.

I am trying to see how I can take the correct predictions from either of these algorithms and sort them by some arbitrary features that I will engineer, but all I am wondering at the moment is how to integrate a sorting algorithm in the first place into the output of a classification algorithm.

**Tags:** neural-networks, machine-learning, classification, ensemble-learning, random-forests


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