Would traditional ML approaches benefit from a feedback loop (a la backprop)?
0
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Would classical ML approaches such as SVMs, RF etc. benefit by having some sort of feedback mechanism (similar to backpropagation in Deep learning)? If so, how can one go about it? Is there any ongoing research in this space?
machine-learning backpropagation
asked 2 days ago
SantinoSantino
62
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add a comment |
0
$begingroup$
Would classical ML approaches such as SVMs, RF etc. benefit by having some sort of feedback mechanism (similar to backpropagation in Deep learning)? If so, how can one go about it? Is there any ongoing research in this space?
machine-learning backpropagation
asked 2 days ago
SantinoSantino
62
$endgroup$
$begingroup$
Could you describe your question in other words? Backprop is more complected algorithm of simple gradient changes where other type just based on gradient changes from cost functions (SVM for ex.).
$endgroup$
– GensaGames
2 days ago
$begingroup$
Sorry my english is not great, but my question is more directed toward some kind of feedback mechanism during training that improves accuracies. Backprop was a big factor for the leap of accuracy in NNs, can (conceptually speaking) backprop-like mechanisms be implemented for classical ML. Hope that clarifies.
$endgroup$
– Santino
2 days ago
add a comment |
0
0
0
$begingroup$
Would classical ML approaches such as SVMs, RF etc. benefit by having some sort of feedback mechanism (similar to backpropagation in Deep learning)? If so, how can one go about it? Is there any ongoing research in this space?
machine-learning backpropagation
asked 2 days ago
SantinoSantino
62
$endgroup$
Would classical ML approaches such as SVMs, RF etc. benefit by having some sort of feedback mechanism (similar to backpropagation in Deep learning)? If so, how can one go about it? Is there any ongoing research in this space?
machine-learning backpropagation
machine-learning backpropagation
asked 2 days ago
SantinoSantino
62
asked 2 days ago
SantinoSantino
62
asked 2 days ago
SantinoSantino
62
asked 2 days ago
SantinoSantino
62
asked 2 days ago
SantinoSantino
62
62
$begingroup$
Could you describe your question in other words? Backprop is more complected algorithm of simple gradient changes where other type just based on gradient changes from cost functions (SVM for ex.).
$endgroup$
– GensaGames
2 days ago
$begingroup$
Sorry my english is not great, but my question is more directed toward some kind of feedback mechanism during training that improves accuracies. Backprop was a big factor for the leap of accuracy in NNs, can (conceptually speaking) backprop-like mechanisms be implemented for classical ML. Hope that clarifies.
$endgroup$
– Santino
2 days ago
add a comment |
$begingroup$
Could you describe your question in other words? Backprop is more complected algorithm of simple gradient changes where other type just based on gradient changes from cost functions (SVM for ex.).
$endgroup$
– GensaGames
2 days ago
$begingroup$
Sorry my english is not great, but my question is more directed toward some kind of feedback mechanism during training that improves accuracies. Backprop was a big factor for the leap of accuracy in NNs, can (conceptually speaking) backprop-like mechanisms be implemented for classical ML. Hope that clarifies.
$endgroup$
– Santino
2 days ago
$begingroup$
Could you describe your question in other words? Backprop is more complected algorithm of simple gradient changes where other type just based on gradient changes from cost functions (SVM for ex.).
$endgroup$
– GensaGames
2 days ago
$begingroup$
Could you describe your question in other words? Backprop is more complected algorithm of simple gradient changes where other type just based on gradient changes from cost functions (SVM for ex.).
$endgroup$
– GensaGames
2 days ago
$begingroup$
Sorry my english is not great, but my question is more directed toward some kind of feedback mechanism during training that improves accuracies. Backprop was a big factor for the leap of accuracy in NNs, can (conceptually speaking) backprop-like mechanisms be implemented for classical ML. Hope that clarifies.
$endgroup$
– Santino
2 days ago
$begingroup$
Sorry my english is not great, but my question is more directed toward some kind of feedback mechanism during training that improves accuracies. Backprop was a big factor for the leap of accuracy in NNs, can (conceptually speaking) backprop-like mechanisms be implemented for classical ML. Hope that clarifies.
$endgroup$
– Santino
2 days ago
add a comment |
0
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$begingroup$
Could you describe your question in other words? Backprop is more complected algorithm of simple gradient changes where other type just based on gradient changes from cost functions (SVM for ex.).
$endgroup$
– GensaGames
2 days ago
$begingroup$
Sorry my english is not great, but my question is more directed toward some kind of feedback mechanism during training that improves accuracies. Backprop was a big factor for the leap of accuracy in NNs, can (conceptually speaking) backprop-like mechanisms be implemented for classical ML. Hope that clarifies.
$endgroup$
– Santino
2 days ago