Why don't we use training/observation data's vector similarity for building models on Tabular data? or if we...
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Considering , we get a new observation, we try to find a 100 similar vectors from the training data and average the labels from them to get the prediction.
machine-learning vector-space-models
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Considering , we get a new observation, we try to find a 100 similar vectors from the training data and average the labels from them to get the prediction.
machine-learning vector-space-models
New contributor
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It is done, it is called clustering. Look for KNN or K-mean algorithms.
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– Mark.F
14 hours ago
add a comment |
$begingroup$
Considering , we get a new observation, we try to find a 100 similar vectors from the training data and average the labels from them to get the prediction.
machine-learning vector-space-models
New contributor
$endgroup$
Considering , we get a new observation, we try to find a 100 similar vectors from the training data and average the labels from them to get the prediction.
machine-learning vector-space-models
machine-learning vector-space-models
New contributor
New contributor
New contributor
asked 15 hours ago
Sidharth MallickSidharth Mallick
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It is done, it is called clustering. Look for KNN or K-mean algorithms.
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– Mark.F
14 hours ago
add a comment |
$begingroup$
It is done, it is called clustering. Look for KNN or K-mean algorithms.
$endgroup$
– Mark.F
14 hours ago
$begingroup$
It is done, it is called clustering. Look for KNN or K-mean algorithms.
$endgroup$
– Mark.F
14 hours ago
$begingroup$
It is done, it is called clustering. Look for KNN or K-mean algorithms.
$endgroup$
– Mark.F
14 hours ago
add a comment |
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It is done, it is called clustering. Look for KNN or K-mean algorithms.
$endgroup$
– Mark.F
14 hours ago