All Questions
Tagged with euclidean-distance cosine-similarity
30
questions
11
votes
3
answers
10k
views
How to get cosine distance between two vectors in postgres?
I am wondering if there is a way to get cosine distance of two vectors in postgres.
For storing vectors I am using CUBE data type.
Below is my table definition:
test=# \d vectors ...
- 3,077
5
votes
1
answer
3k
views
Best way to identify dissimilarity: Euclidean Distance, Cosine Distance, or Simple Subtraction?
I'm new to data science and am currently learning different techniques that I can do with Python. Currently, I'm trying it out with Spotify's API for my own playlists.
The goal is to find the most ...
- 337
4
votes
1
answer
2k
views
Calculating similarity based on attributes
My objective is to calculate the degree of similarity between two users based on their attributes. For instance let's consider a player and consider age, salary, and points as attributes.
Also I ...
- 2,088
3
votes
4
answers
7k
views
How to find most optimal number of clusters with K-Means clustering in Python
I am new to clustering algorithms. I have a movie dataset with more than 200 movies and more than 100 users. All the users rated at least one movie. A value of 1 for good, 0 for bad and blank if the ...
- 61
3
votes
1
answer
2k
views
Does Euclidean Distance measure the semantic similarity?
I want to measure the similarity between sentences. Can I use sklearn and Euclidean Distance to measure the semantic similarity between sentences. I read about Cosine similarity also. Can someone ...
- 71
3
votes
1
answer
1k
views
Distance calculation in mongodb aggregate using cosine
I am saving face embedding as numpy array in mongodb and using this aggrigate to find distance between to array using euclidean algorithm.
Can someone please help to calculate distance using cosine?
...
- 870
3
votes
1
answer
617
views
Calculate Distance Metric between Homomorphic Encrypted Vectors
Is there a way to calculate a distance metric (euclidean or cosine similarity or manhattan) between two homomorphically encrypted vectors?
Specifically, I'm looking to generate embeddings of documents ...
- 542
3
votes
1
answer
2k
views
How to calculate weighted similarity with scipy.spatial.distance.cosine?
From the function definition:
https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cosine.html
scipy.spatial.distance.cosine(u, v, w=None)
but my codes got some errors:
from ...
- 55
3
votes
0
answers
3k
views
Normalising Data to use Cosine Distance in Kmeans (Python)
I am currently solving a problem where I have to use Cosine distance as the similarity measure for Kmeans clustering. However, the standard Kmeans clustering package (from Sklearn package) uses ...
- 4,344
2
votes
0
answers
631
views
Find top five similar image using cosine similarity
I have a feature list of images with length n.
feature_list -> [array[img1], array[img2]....n]
I can find top 5 using sklearn.neighbors.NearestNeighbors. by following
neighbors = NearestNeighbors(...
- 109
2
votes
1
answer
4k
views
Euclidean Distance or cosine similarity? [closed]
I was reading
Similarity Measure
and suddenly my whole world was falling apart. I have implemented a search engine using Clustering Technique. For Clustering , I used K Means which has distance ...
- 721
1
vote
1
answer
3k
views
How to calculate Cosine similarity and Euclidean distance between two tensors in TF2.0?
I have two tensors (OQ, OA) with shapes as below at the end of last layers in my model.
OQ shape: (1, 600)
OA shape: (1, 600)
These tensors are of type 'tensorflow.python.framework.ops.Tensor'
How ...
- 457
1
vote
2
answers
2k
views
Get indices of results from scipy.pdist(myArray,metric="jaccard") to map back to original array?
I am trying to calculate jaccard similarity
y= 1 - scipy.spatial.distance.pdist(X,metric="jaccard")
X is a m x n matrix and I get a 1-D array of size m choose 2 as a result of this function. How ...
- 12k
1
vote
1
answer
1k
views
Finding most similar items by euclidean and cosine
How do I go about finding similarities in R? In particular, the similarity metrics I care most about are cosine and a KNN-# value. I guess the key aspect of this is so that the data comes out in a ...
- 6,425
1
vote
2
answers
1k
views
Correctly interpreting Cosine Angular Distance Similarity & Euclidean Distance Similarity
As an example, let's say I have a very simple data set. I am given a csv with three columns, user_id, book_id, rating. The rating can be any number 0-5, where 0 means the user has NOT rated the book.
...
- 177
1
vote
1
answer
183
views
How to convert TS-SS result to similarity measure between 0 - 1?
I'm currently developing a question plugin for some LMS that auto grade the answer based on the similarity between the answer and answer key with cosine similarity. But lately, I found that there is a ...
- 105
1
vote
0
answers
221
views
Pyspark Euclidean and Cosine distance between 2 arrays
I have a pyspark data frame with data shaped like the following (data made up):
Dataframe
I would like to calculate various distance metrics (such as cosine, euclidean) between the 2 vectors, vec1 ...
- 11
1
vote
0
answers
60
views
distance calculation whan Nan is the maximum possible distance
I really tried my best to find a solution to my problem. Given that I have 2 customers with several attributes as given below;
cust1 = [4.0, 75.0, 2.0, 155.0, 58.0, 3.0, 7.0, 4.0, 0.0, 4.0, 0.0, 1.0, ...
- 21
1
vote
1
answer
782
views
Using relative frequency for euclidean distance
How do I calculate the euclidean distance(similarity) between two documents eg D1 and D2 using relative frequency?.
Below is an example of both cosine and euclidean distance between two documents ...
user2100552
1
vote
2
answers
225
views
Similarity of documents function
I am trying to create matrices for cosine and euclidean distances of a document. not too sure how I would approach this question. Any advice would be appreciated. Thanks.
The function takes the ...
- 43
0
votes
1
answer
450
views
Weighted Euclidean Distance while Merging Feature Vectors?
I have two groups of features (describing an image, in a machine learning context). The first group A, consisting of 3 features, and group B consisting of 15 features.
A = [f1, f2, f3]
B = [f4, f5, ..,...
- 807
0
votes
1
answer
874
views
Euclidean vs Cosine for text data
IF I use tf-idf feature representation (or just document length normalization), then is euclidean distance and (1 - cosine similarity) basically the same? All text books I have read and other forums, ...
- 445
0
votes
1
answer
429
views
R studio: Is there a way to calculate the cosine & euclidean distance between 2 time series with a single & multiple variables of interest?
Let's say I have time series data of City A, City B, City C & City D that looks like this:
+------------+--------+--------+--------+--------+
| Dates | City A | City B | City C | City D |
+---...
- 431
0
votes
1
answer
373
views
Similarity Metrics
I am trying to research on different metrics and found many ssimilarity metrics : Euclidean distance Dynamic Time Warping, Edit Distance with Real
Penalty DISSIM , Sequence Weighted Alignment model, ...
- 45
0
votes
1
answer
189
views
Why do my t-SNE plots with euclidean and cosine distances look similar
I have a question about two t-SNE plots I made.
I have a set of 850 articles for which I wanted to check which articles are similar to each other.
This was done by pre-processing the articles first, ...
- 21
0
votes
0
answers
166
views
Smart Semantic Category Clustering Using R
Got 2 data frames, did the below:
library(tm)
v<- Corpus(VectorSource(as.vector(bothsources[,1])))
inspect(head(v,3))
v <- tm_map(v, removeWords, stopwords("english"))
v <- tm_map(v, ...
- 43
0
votes
0
answers
816
views
Is there any package in R to use jaccard or cosine distance for k-medoid clustering?
I am using function pam in package cluster for partitioning around medoids.
pam(x, k, diss = inherits(x, "dist"), metric = "euclidean",
medoids = NULL, stand = FALSE, cluster.only = FALSE,
...
- 4,082
0
votes
1
answer
76
views
Good similarity measure for comparing users
I want to compare users based on responses to 10 questions. My original idea was to resolve each question to an integer [1, 5], but this idea won't work all the time. For example:
vec1 = [1,1,1,1,1,1,...
- 2,662
0
votes
1
answer
1k
views
There are other useful similarity or distance metrics?
I'm developing an approximate computation system. Defining how much similar two objects are is a basic operation in such a system.
Usually in computer science and math, similarity is synonym of ...
- 6,648
0
votes
2
answers
2k
views
Measuring distance between vectors
I have a set of 300.000 or so vectors which I would like to compare in some way, and given one vector I want to be able to find the closest vector I have thought of three methods.
Simple Euclidian ...
- 393