All Questions
Tagged with numpy clustering
19 questions
6
votes
1
answer
584
views
Schelling's model of Segregation Python implementation with Geopandas
If you don't know what is Schelling's model of segregation, you can read it here.
The Schelling model of segregation is an agent-based model that illustrates how individual tendencies regarding ...
- 255
5
votes
2
answers
5k
views
Grouping sorted coordinates based on proximity to each other
I created an algotrithm that groups a sorted list of coordinates into buckets based on their proximity (30) to one another.
Steps:
Create a new key with a list ...
- 153
3
votes
0
answers
543
views
Locality Sensitive Hash (similar to k-Nearest Neighbor), in Python+Numpy
I've tried implementing Locality Sensitive Hash, the algorithm that helps recommendation engines, and powers apps like Shazzam that can identify songs you heard at restaurants.
LSH is supposed to run ...
- 187
5
votes
1
answer
6k
views
k-means using numpy
This is k-means implementation using Python (numpy). I believe there is room for improvement when it comes to computing distances (given I'm using a list comprehension, maybe I could also pack it in a ...
- 381
1
vote
0
answers
7k
views
Fuzzy c Means in Python
This is my implementation of Fuzzy c-Means in Python. In the main section of the code, I compared the time it takes with the sklearn implementation of kMeans.
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- 195
2
votes
0
answers
240
views
Calculation of clustering metric in Python
When I try to run the following code for arrays with more than 10k elements, it takes hours and I don't know how to make it in the most efficient way.
Any ideas?
...
- 21
7
votes
1
answer
164
views
Speeding up maximum self-similarity test for heavy tail-exponents
I am trying to reproduce results from a research paper using python. I've checked my method and it works on relatively small sample datasets. However, the code does not run for my actual dataset, ...
user127168
5
votes
1
answer
599
views
Clustering points on a sphere
I have written a short Python program which does the following: loads a large data file (\$10^9+\$ rows) where each row is a point on a sphere. The code then loads a pre-determined triangular grid on ...
- 309
1
vote
1
answer
4k
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Cosine similarity computation
I have a matrix of ~4.5 million vector [4.5mil, 300] and I want to calculate the distance between a vector of length 300 against all the entries in the matrix.
I got some great performance time ...
- 51
4
votes
1
answer
3k
views
OpenCV 3: Using k-Nearest Neighbors to analyse RGB image
I'm new to computer vision and numpy.
I wrote a simple script to seperate red, green and blue colors from the original image by using the kNN algorithm.
After reading through some numpy tutorials, I'...
- 203
7
votes
1
answer
6k
views
k-means clustering algorithm implementation
Here is my personal implementation of the clustering k-means algorithm.
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10
votes
1
answer
14k
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2
votes
1
answer
362
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Neighbours from point connections
I am working with a mesh of triangles (in 3D, although I doubt it makes a difference). The mesh is given as list of lists, each list containing the indices of the three vertices of a triangle in said ...
- 309
4
votes
1
answer
5k
views
Calculating the distance between one point, and many others
In my program, I have entities that I call "blobs", because they have a blobby shape. Blobs are polygons. If I have two blobs, then their information array would look like:
...
- 399
14
votes
2
answers
9k
views
Possible optimizations for calculating squared euclidean distance
I need to do a few hundred million euclidean distance calculations every day in a Python project.
Here is what I started out with:
...
- 243