Questions tagged [distance]
For question regarding distance between distributions or variables, such as Euclidean distance between points in n-space.
145 questions
7 votes
0 answers
71 views
How can I measure the similarity between distance matrices during embedding training?
I am studying how the distances between embeddings evolve during training of a language model. One way to describe this "evolution" is that the k-nearest neighbours of a particular embedding ...
- 7,521
1 vote
0 answers
81 views
How to Determine the Optimal Number of Clusters / distance threshold in Agglomerative Clustering Using a Connectivity Matrix?
I am working on agglomerative clustering with the goal of ensuring continuity among clusters. To achieve this, I am using a connectivity matrix to enforce certain continuity constraints. However, it ...
- 11
0 votes
1 answer
31 views
How set binary random projection to features, num_samples for X-train, x_test, y_train to match knn distances L dimension
Binary Random Projection of Features, Samples Creating a binary random projection that will be used in a kNN Hanning function for hamming distances on nearest neighbors that will be processed by ...
0 votes
1 answer
267 views
Standard metric for distance between two clusters
Let $A=\{A_1,A_2,\cdots,A_m\}$ and $B=\{B_1,B_2,\cdots,B_n\}$ be two sets of points in $k$-dimensional Euclidean space. Each points $A_i$ or $B_i$ can be thought of as a feature vector of a data ...
- 101
1 vote
0 answers
72 views
What is the l2-norm of a scalar
What is the meaning of the l2-norm when dealing with scalar values? I'm assuming it would be the same thing as taking the absolute value. For context: I am trying to implement the clustering method ...
1 vote
0 answers
67 views
In WGAN paper, why does clipping weights approximate Lipschitz function?
In Wasserstein GAN, it's explained that maximizing a certain formula over a set of K-Lipschitz functions approximates the 1-Wasserstein distance and they model the functions as NNs. That much I ...
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1 vote
1 answer
687 views
In DBSCAN, can the distance between a Noise Point and Border Point be less than Epsilon?
In DBSCAN: A core point is a point which has at least "MinPts" points inside its Epsilon radius. A border point is a point inside the Epsilon radius of a core point, but it has a number of ...
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3 votes
1 answer
163 views
What justifies feature scaling?
Although I can understand the significance of feature scaling in some cases (e.g. when gradient descent is involved), I don't feel I understand the necessity of this process in general. But there a ...
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