Questions tagged [distance]

For question regarding distance between distributions or variables, such as Euclidean distance between points in n-space.

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Bottleneck Distance

Is there a range of values for the bottleneck distance in persim package (python) to conclude that the two datasets are similar? Also, does it make sense to compute the bottleneck distance using $H_0$ ...
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12 views

Pairwise 3D object correlation between 2 objects

I have a dataset which contains 3D CT scans from different patients along with the segmenation masks of a certain organ. The 3D scans have been drawn each day for a period of 30 days for each patient. ...
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14 views

Calculate distance ignoring Outliers

I have the GPS Coordinates of a person performing an activity. The activity has a start GPS point, start time and end GPS point, end time. The rule is that the difference between the start GPS point ...
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1answer
11 views

How to measure the distance (in generalized sense) between geographical regions? [closed]

I need to construct a distance matrix for a few U.S. counties that are adjacent to one or another, and choosing the definition of distance is very tricky. The shortest path (i.e the minimum number of ...
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1answer
17 views

Clustering without information about identifier

I have a data-set with different products and binary value if it was sold in a store or not. I looks like: ...
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2answers
96 views

How do I test a difference between two proportions representing fatality rate for Covid 19 in Philippines and World (except Philippines)?

I'm trying to analyse if the fatality rate from my country (A third world country) vary significantly from the world's fatality rate. So I'd basically have two samples, labeled (Philippines) and (...
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Learnable distance measure for segments of periodic multichannel signal?

We have a set of users, each with several sessions, each session represented as multichannel signal. Users behave differently, but if we visualize several sessions of the same user we can often see a ...
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4answers
275 views

Clustering algorithm which does not require to tell the number of clusters

I have a dataframe with 2 columns of numerical values. I want to apply a clustering algorithm to put all the entries into the same group, which have a relatively small distance to the other entries. ...
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1answer
25 views

Very basic question: what is an accepted term for “linear order distance”

In data science we have "Manhattan Distance" as a slang term for Level 1 Distance and "Euclidean Distance" as a slang term for Level 2 Distance. Is there an accepted term for linear distance in memory ...
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3answers
80 views

Cluster elements that appear in the same lists

Suppose I have a multitude of sets with (unordered) combinations of elements and I want to determine which elements tend to appear together. For example Given the following sets: ...
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23 views

How to have an insight of very similar processing methods by measuring the distance between observations produced by them? [closed]

Suppose that we use very similar methods(suppose now there are two such similar methods) to process upon each sample of a dataset. For each sample of the dataset with one of the two methods, we obtain ...
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1answer
27 views

Some robust perhaps more complex as neural networks to measure the distance between data? [closed]

Now after certain preprocess we can repeatedly get two sets of data points, exhaustively enumerate one from the first set and one from the second set to form pairs. Each pair of these two data points ...
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2k views

How to evaluate the K-Modes Clusters?

K-modes algorithm is available here I want to do clustering of my binary dataset. I need to specify the number of clusters that I need as an output: ...
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67 views

Voronoi Diagram Algorithm for Geo Locations? [closed]

As per my Understanding: Voronoi diagram: A Voronoi diagram is a simple concept, and it's based on the minimal distance needed to reach a landmark. If you need to go to a metro station, the most ...
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26 views

Random Forest proximity matrix with or without in bag samples

I'm running Random Forest classifications; and PCA plots based on the resulting proximity matrices are quite helpful to my analyses. However, I found a comment on the R ...
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10 views

How to quickly find min, max and mean distance between samples fitted in Nearest Neighbors?

I am familiar only with SciKit Learn implementation of Nearest Neighbors model where one can fit data and execute K-neighbors or radius queries. This model does not provide any statistical information ...
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2answers
371 views

Question about Similarity vs Dissimilarity Matrix

Right now, I'm working on a coming up with a similarity vs dissimilarity matrix for a set of data points for a clustering algorithm. My question is, if I want to use one of the many clustering ...
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34 views

Question About Coming Up With Own Function for Distance Matrix (For Clustering)

Right now, I am currently working on implementing a clustering algorithm with millions data entries with regards to game users for a mobile game. A lot of the features I plan on using are unique to ...
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13 views

Finding the closest neighbour of multidimensial data point

I have a test point with 15 attributes. I want to find the closest data point to this test point from 10,000 data points. I'm thinking using something like this: ...
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53 views

How to calculate Fuzzy C-Means problem by hand

I figured that this doubt next can interest another students like me and help others also that are trying to understand mathematically the fuzzy c-means mathematical mechanism already that some books ...
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1answer
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It seems that the output of sklearn.metrics.pairwise.euclidean_distances is different to the formula on doc

The doc of sklearn.metrics.pairwise.euclidean_distances() gives this formula dist(x, y) = sqrt(dot(x, x) - 2 * dot(x, y) + dot(y, y)). Apply this formula to ...
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What options do I have for measuring similarities by using vectors generated from texts?

I have a data set which contains vectors generated from subtitles, I want to measure the similarity between each pair of the observation. Now I have tried L1, L2, cosine similarity and Mahalanobis ...
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38 views

Is it necessary to perform Z-score or Min-Max normalization on L1-normalized data?

I have a dataset which contains vectors that generated from subtitles and have been L1 normalised, I want to calculate cosine similarity & Euclidean distance, I thought it is better if I use Z-...
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1answer
224 views

values passed to user-defined distance function by KNeighborsClassifier is wrong

I have a data-set in which all features are binary and the class of each data-point is also binary. I am trying to use KNearestClassifier with a user-defined distance function as follows: ...
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47 views

CNN Architecture for Measuring Object Distances

I'm trying to use CNNs for infering object distances from an image. The input images correspond to states of a 2D game: Game states are not represented as images but as matrixes of observations. ...
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18 views

Is there any paper introduce an intuitive method for clustering evaluation?

I would like to use the most intuitive method like minimizing the within-cluster distance and maximizing the distance between neighbouring clusters, but not sure does this method have a name or ...
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1answer
67 views

Is the distance in Nearest Neighbors a good measure of similarity?

Let's train a Nearest Neighbor model with just one sample in it: In [48]: nn = NearestNeighbors().fit([[0, 1, 0, 0]]) So this one sample has just one significant ...
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346 views

Finding linear transformation under which distance matrices are similar

I have $n$ sets of vectors, where each set $S_i$ contains $k$ vectors in $\mathbb{R}^d$. I know there is some unknown linear transformation $W$ under which the distance matrix $D_i$ (a $k\times k$ ...
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101 views

Cluster based on both positions and similarity scores

I have a dataframe position giving me the x and y positions of 87 points. I also have a 87 x 87 similarity matrix giving me the pairwise similarity scores between ...
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4answers
92 views

Estimating time to travel between two lat/longs

I'm trying to create an offline estimator for how long it would take to get from one lat/long to another. Two approaches I have come across are the Haversine distance and the Manhattan distance. What ...
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2answers
49 views

Reverse engineering a distance metric from the output of a k-NN

Suppose that someone has trained a nearest-neighbor algorithm based on some unknown metric. I have a large dataset of $N$ observations and $P$ features. For each observation, I am given $K$ indices ...
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32 views

Features Vectors in embedding space

I have a bunch of users, each of them with about 100 features. My goal is to create an embedded space to compute the "distance" between users. Also, I want to be able to visualize it with Tensorboard (...
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6answers
238 views

Distance between users

I want to compute the "distance" between users in order to return the top n similar users, for any given user. For each user a have a bunch of features. This is close to a recommendation system, ...
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1answer
245 views

Coordinate System's influence on $L$ distances (Manhattan and Euclidean)

I don't understand this picture, which says if we change the coordinate system, we would have the same result for $L_2$ distance, whereas, our result would differ for $L_1$ distance. What does it ...
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63 views

What is divergence exactly in machine learning?

I know about KL divergence, JS Divergence and clearly know that it is different from the divergence in calculus. I have an intutive feeling of divergence as it roughly compares the closeness of two ...
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2answers
445 views

Measuring distance preservation in dimensionality reduction

I am looking to compare the distance preserved during dimension reductions for several techniques. I have read some papers on similar topics here and here. For example, I would like to use the ...
4
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1answer
510 views

K Nearest Neighbour with different distance matrix to each datapoint

I'm wondering if there is library support in python (such as sklearn) for doing KNN on a data set that has a custom distance matrix (positive definite) for each data point (x is a query point, $x_i$ ...
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1answer
1k views

What does sklearn's pairwise_distances with metric='correlation' do?

I've put different values into this function and observed the output. But I can't find a predictable pattern in what is being outputed. Then I tried digging through the function itself, but its ...
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1answer
170 views

scipy.spatial.distance.mahalanobis return null values for some vectors in python

I am using scipy.spatial.distance.mahalanobis to calculate distance between two vectors but i'm getting null values for some vector I don't know why? null value is possible?
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1answer
1k views

How to measaure the similarity between two series?

I'm confused about how to measure the similarity between two time series with the same length. For example, both time series are 2 hours in length and every 5 minutes a point. I really want to know ...
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1answer
36 views

Date transformation for KNN to get distance [duplicate]

I have data set with date features like 01/01/2019 and I would like to use KNN. However, I cannot find a good transformation for dates that has a meaningful distance result for the last feature. For ...
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2answers
109 views

Date transformation for KNN

I have data set with date features like 01/01/2019 and I would like to use KNN. However, I cannot find a good transformation for dates that has a meaningful ...
2
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1answer
42 views

Positive semidefinite kernel matrix from Gower distance

I have a dataframe with continuous and categorical variables and I want to obtain a kernel matrix for classification. The kernel matrix must be symmetric and positive semidefinite, so that no ...
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3answers
148 views

Are there algorithms for clustering objects with pairwise distances, without computing all pairwise distances?

I'm looking for a clustering algorithm that clusters objects, by using their pairwise distances, without needing to calculate all pairwise distances. Normally pairwise clustering is done like this: (...
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3answers
2k views

Clustering algorithm for a distance matrix

I have a similarity matrix between N objects. For each N objects, I have a measure of how similar they are between each others - 0 being identical (the main diagonal) and increasing values as they get ...
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3answers
59 views

Match a two items from two different receipts

I have two different invoices or receipts. One is a Purchase order one is something like a receipt(acknowledgement). Suppose I have ordered(PO) Wine: White Wine Red Wine Rose Wine And I receive ...
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Which distance method will account for positions of observations in arrays?

I am trying to figure out the distance method suited for my problem. I have different arrays of the same length. Each position in the array matters. Let's say ... each array is representing an image, ...
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1answer
31 views

Is there a way to cluster words based on how similarly they sound?

I have a list of words for a fictional world I've made (don't judge lol). My ultimate goal is to generate more words that sound like them through a markov generator, but for now, I'm trying to build ...
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1answer
121 views

Clustering time series based on monotonic similarity

Context I am involved in a task of clustering 1500 time series of 500 observations into a few number of clusters. The time series share all the same observed property at different spatial locations, ...
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3answers
79 views

A metric between trees

I have certain tree structures. I am not an expert in machine learning. As I would with take KNN, I would calculate distances via metric function and a new data point and the points from the training ...