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For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

1 vote

Is it possible to flip the features and labels after training a model?

The body of your post seems to be asking a completely separate question than the title of your post, so I will answer both: "Body: How do I complete the goal of this program?" Your dataset does not ha …
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1 vote

What does "adding class weights for an imbalanced dataset" mean in the case of multi-label c...

The paper A systematic study of the class imbalance problem in convolutional neural networks is a great overview on class imbalance approaches. Section 2 summarizes various methods commonly used. They …
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1 vote

Why does k-means have more bias than spectral clustering and GMM?

I'm not an expert on clustering, but here's my take below. Note that this is only based on theoretical arguments, I haven't had enough clustering experience to say if this is generally true in practic …
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12 votes
Accepted

Why does this multiplication of $Q$ and $K$ have a variance of $d_k$, in scaled dot product ...

In statistics, if $X$ and $Y$ are independent and randomly distributed variables: $\mathbb{E}[X + Y] = \mathbb{E}[X] + \mathbb{E}[Y] \\ Var(X + Y) = Var(X) + Var(Y) \\ \mathbb{E}[XY] = \mathbb{E}[X]\m …
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