Questions tagged [distance]
For question regarding distance between distributions or variables, such as Euclidean distance between points in n-space.
2
votes
1answer
16 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 ...
1
vote
3answers
28 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: (...
1
vote
2answers
30 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 ...
0
votes
0answers
12 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 ...
1
vote
0answers
16 views
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, ...
2
votes
1answer
15 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 ...
2
votes
1answer
25 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, ...
2
votes
3answers
33 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 ...
1
vote
1answer
83 views
Why don't we use Manhattan distance instead of euclidean distance in linear regression?
When I am explaining concept of linear regression to one of my peers, I got stuck in answer this question. Why don`t we use Manhattan distance instead of euclidean distance in linear regression? Can ...
0
votes
1answer
33 views
How can i use Hellinger Distance on array of different length?
I have to use Hellinger distance to compare arrays that are not of the same length.
Is there a way to do it correctly? Put zero in the missing fields of the shorter array doesn't sound that good to me ...
1
vote
2answers
152 views
How can I implement tangent distance for k-nearest neighbor in python/scikit-learn?
My ultimate aim is to have a function which I can feed into scikit-learn's NearestNeighbor class as a custom metric parameter.
...
0
votes
2answers
80 views
Nearest Neighbors on mixed data types in high dimensions
I would like to be able to use nearest neighbors to attempt to find the most similar samples to a subclass of samples (think treated vs untreated) in a dataset with continuous, categorical, and text ...
1
vote
0answers
9 views
How to generate multiple vectors given their distances [closed]
Well, the title says it all. I'm looking for an algorithm that would generate multiple random vectors with given distances between them.
Any suggestions?
1
vote
1answer
93 views
Calculation of distance between samples in data mining
I am confused about a little issue related to distance calculation. What I want to know is, while calculating the distance between samples in classification or regression, is the label or output class ...
2
votes
2answers
84 views
Meaning of axes in a clustering plot
If you have n time series of rainfall measurements every hour (x=time, y=amount of rain), and compute the distance matrix between each pair of time series based on Dynamic Time Warping, and then plot ...
1
vote
1answer
54 views
Minkowski distance with Missing Values
Im currently doing a subject for data science, and have the following point that im trying to understand.
We are looking to calculate distance in data sets where values may not be present. Now i ...
1
vote
0answers
47 views
Proximity distance between two strings
How can I calculate the proximity between two strings
Ex: I need to find all the names in unstructured text and also need to look if there is any given string (i.e 'title') nearby
Input:
'...
1
vote
1answer
26 views
Appropriate similarity measure that highlights symmetrical values of features
I am trying to find an appropriate distance measure that reflects the differences of the vectors seen in the image below:
The green vector is compared with the blue one and the orange one.
Most of ...
2
votes
3answers
133 views
clustering 2-dimensional euclidean vectors - appropriate dissimilarity measure
I've got a set of approx. 50 000 2-dimensional euclidean vectors which are connected with 20 groups, i.e. each group has approx. 2500 2-dimensional euclidean vectors. My data includes endpoints ...
4
votes
3answers
70 views
Distance between very large discrete probability distributions
I have 192 countries where each country has some value for 1 million attributes which sum up to 1 (a discrete probability distribution). For any one country most of the values for the attributes are 0....
1
vote
0answers
64 views
advice on distance metric for knn w/image recognition
I'm getting my feet wet with machine learning and am implementing a knn algorithm on a dataset that i've created. I've created a set of images of circles and squares and want the knn algorithm to ...
1
vote
1answer
25 views
Euclidean distance for more than 2 datapoints
I need to compare $n$ 3-dimensional vectors with $k$ 3-dimensional vectors using euclidean distance. Is that possible?
1
vote
1answer
29 views
Euclidean distance for more than two datapoints
I have n 3-dimensional vectors. Is there a way to find distance between all using euclidean distance?
0
votes
1answer
19 views
Voting patterns similarities
I'm interested in any research materials on voting patterns.
I have a data set of how PMs (members of parliament) voted in my country during last couple of years. Each PM has 3 buttons: Yes, No, ...
2
votes
1answer
2k views
How to calculate the silhouette coefficient?
Calculate the silhouette coefficient of point Pi from the above image.
To apply the given formula, how to know which is a(i) and b(i)?
2
votes
1answer
883 views
Knn and euclidean distance
I'm studying the knn classification algorithm.
Why can the euclidean distance be considered a nice measure of affinity between examples ?
In one dimension (1 attribute) this seems correct, but if I ...
1
vote
0answers
34 views
Suitability of Jaccard's distance for count vectorized features
I had an assignment in which we had to classify the cuisine and also give back the top-5 recipes based on given input. I did a count vectorization (countVectorize.transformer()) for the following data ...
2
votes
1answer
160 views
How can I measure the similarity between 2 IP addresses? Is there any code to re-use?
I need to measure the similarity of 2 IP addresses. I could not find any sample code in scala or other languages to find the distance between 2 IPs.
0
votes
0answers
75 views
How to better visualizing Earth Mover Distance in relation with generative adversarial networks?
After reading the original EMD paper from 1998 I am having a hard time trying to visualize the connections between their dirt pile example to generative adversarial networks. Everything is kind of ...
5
votes
2answers
848 views
Alternative distance to Dynamic Time Warping
I am performing a comparison among time series by using Dynamic Time Warping (DTW). However, it is not a real distance, but a distance-like quantity, since it doesn't assure the triangle inequality to ...
3
votes
1answer
51 views
Statistically Robust Distance Measure/Metric for comparing more than two network data series
I have about 30 lists of unequal length (some of which are triplicates of the data), corresponding to metrics relating to nodes of different graphs. I want to compare their similarity using a distance ...
3
votes
2answers
600 views
How the squared Euclidean distance is an example of non-metric function?
I am reading a book on Pattern Recognition (by Prof V Susheela Devi and Prof Murty) where in the chapter of data representation 2.3.3 the non metric similarity function is defined as those which do ...
2
votes
1answer
122 views
How to build an encoder using a distance matrix
I have a similarity/distance matrix:
a | b | c
a 0 | 1 | 2
b 1 | 0 | 3
c 2 | 3 | 0
I want to build an encoder/model that learns an n-dimensional ...
3
votes
2answers
84 views
Collection Of Variable Length Sequences and Descriptions: A Search Problem
I have a tough problem and need some advice:
Suppose I have a collection of variable length sequences, many of which are unique -- imagine the moves to a chess game, eg
d4 Nf6
c4 g6
Nc3 Bg7
...
0
votes
1answer
356 views
What are similarity and distance metrics in classification?
I have an assignment to train a model to classify text data, the brief for the assignment mentions that any for any learning model used I have to provide a reasoning for the similarity or distance ...
0
votes
1answer
98 views
What is the efficient way to generate a similarity score when comparing two face images?
I am working on a face recognition application using deep learning. To plot the ROC curves and do performance evaluation, I extracted the features from the last layer of the deep neural network and I ...
2
votes
0answers
94 views
How tangent distance works in three-dimentional space
I've read about tangent distance used in machine learning but I don't really know how it works. Concretely, consider two very different manifolds M1 and M2 and two points x1, x2 on that two manifolds ...
0
votes
2answers
1k views
Finding similarity between two histogram plots
I have data census(name, sex, age, capital_gain) and I want to plot all possible views (in a histogram) and find the most interesting view based on the distinction to other views.
So, I have to ...
3
votes
1answer
537 views
Can I use euclidean distance for Latent Dirichlet Allocation document similarity?
I have a Latent Dirichlet Allocation (LDA) model with $K$ topics trained on a corpus with $M$ documents. Due to my hyper parameter configurations, the output topic distributions for each document is ...
-1
votes
2answers
283 views
Assessing Group Similarities and Dissimilarities Post PCA
The goal is to assess similarity and dissimilarity between 6 known groups.
The original data began with the 6 known groups and 2,700+ variables all on a scale of 0 to 100.
I have performed PCA to ...
2
votes
0answers
67 views
Outlier detection: Should the metric used in kNN take into account variance explained by each coordinate?
After applying PCA and working with the reduced dataset, I want to delete the outliers. To do this my idea is to compute the kNN-graph and delete those vertices (points) that have an inner degree of 0....
1
vote
1answer
296 views
Limits of Hellinger distance values
I am calculating Hellinger distance for different vectors. I initially assumed that the value returned by it in in the range of 0 to 1.
However for the following two vectors I received Hellinger ...
18
votes
1answer
4k views
What is Hellinger Distance and when to use it?
I am interested in knowing what really happens in Hellinger Distance (in simple terms). Furthermore, I am also interested in knowing what are types of problems that we can use Hellinger Distance? ...
-1
votes
1answer
52 views
Distance measure calculation addresses for record linking
At the moment we use different methods for record linking locations in different datasets.
Theoretically given two locations we can give a prediction on how well they match (are the same). This is ...
1
vote
1answer
84 views
how to compare two groups
I need to compare two groups of people, where the independent variable is having a college degree, and the dependent variable is the income.
The problem is that if I divide the whole population of ...
1
vote
0answers
21 views
DTW - What is fan-in nodes and why not just take the nearst points from each timeserie?
It has been a while that I am trying to understand the dtw (dynamic time warping) algorithm but I steel can't figure out the loginc behind this algorithm..
In many references it's explained that to ...
2
votes
0answers
438 views
2D Image-based Avatar Animation With Expressions / Image-To-Image Translation
What I want to do
Input an image-sequence (videoframes) that is already cropped and aligned to only the face/hair region and photorealistically replace this Person, Person A (can be anyone, I also ...
9
votes
3answers
12k views
When would one use Manhattan distance as opposite to Euclidean distance?
I am trying to look for a good argument on why one would use the Manhattan distance over the Euclidian distance in Machine Learning.
The closest thing I found to a good argument so far is on this MIT ...
1
vote
2answers
3k views
Multidimensional Dynamic Time Warping Implementation in Python - confirm?
I believe that I implemented MDTW in python here but I don't know if I did it correctly. The results seem intuitive. Can someone look at this code and tell me if you see anything wrong?
A lot of the ...
1
vote
1answer
429 views
How to compare performance of Cosine Similarity and Manhatten Distance?
I'm doing clustering of documents by applying k-Means on the word-vectors. To measure the cluster quality, I calculate David Bouldin Index for different k's. I tried two different distance measures, ...
