Questions tagged [spectral-clustering]
14 questions
12
votes
1 answer
What are practical differences between kernel k-means and spectral clustering?
I've been lately wondering about kernel k-means and spectral clustering algorithms and their differences.
I know that spectral clustering is a more broad term and different settings can affect the way it works, but one popular variant is using…
Kuba_
- 264
- 1
- 10
2
votes
1 answer
Ways of calculating the area of colored regions in a map
Background
I am a PHD student trying to improve my data science. One of my research projects, has me tasked with determining the size of the clusters in a colored image of regions. Here is an example image I am using. The coloring is natural as it…
Gabriel Fair
- 257
- 3
- 8
2
votes
3 answers
What's the fastest clustering package in Python?
I'd like to perform clustering analysis on a dataset with 1,300 columns and 500,000 rows.
I've seen that clustering algorithms are available in SciKit-Learn. But I'm worried that the algorithms will be inefficient on a dataset of this size.
Is…
Connor
- 597
- 1
- 15
1
vote
0 answers
Why kmeans cluster breakup is like this
I have a galaxy spectrum data set (total 22000). Similar to an electronic wave data, two dimensional (Flux vs Wavelength). A typical set of wavelength plot looks like below
Now I am doing kmeans on this data set to cluster them based on their…
Ayan Mitra
- 139
- 4
1
vote
1 answer
Clusterize Spectrum
I have pandas table which contains data about different observations, each one was measured in different wavlength. These observsations are different than each other in the treatment they have gotten.
The table looks something like this:
>>>name …
Reut
- 349
- 2
- 13
1
vote
0 answers
Which version of spectral clustering in sklearn library?
Which version of spectral clustering is implemented in sklearn library? Is it Shi, Malik or Ng, Jordan, Weiss from this tutorial? In sklearn user guide, both versions are mentioned in reference. From the source code, it is not trivial to understand…
Munira
- 157
- 2
- 9
1
vote
1 answer
How to use spectral clustering to predict?
In an academic paper, they talk about using a nearest neighbour algorithm to predict the cluster of a new point. And how the number of nearest neighbours is set to 10 in their example.
What do they mean with this? The two things I could think of…
strateeg32
- 143
- 5
1
vote
1 answer
best algorithms for clustering customers, customer segmentation
I have a dataset mixture of categorical and numerical variable, I was wonder what are the best algorithms to cluster customers?
how to find the underlying patterns that segments a customer??
F.Hazratian
- 13
- 2
1
vote
0 answers
What clustering algorithm is best for dataset with only binary categorical features
I have a dataset with a lot of binary categorical features and a single continuous target value.
I would like to cluster them but I am not quite sure what to use?
I have in the past used dbscan for something similar and it worked well, but that…
Oliver
- 123
- 5
1
vote
1 answer
What are the benefits of using spectral k-means over simple k-means?
I have understood why k-means can get stuck in local minima.
Now, I am curious to know how the spectral k-means helps to avoid this local minima problem.
According to this paper A tutorial on Spectral, The spectral algorithm goes in the following…
Amartya
- 133
- 5
0
votes
1 answer
MEL VS linear spectrograms for bioacoustics machine learning
I don't have background in bioacoustics but working on a data-science project in bioacoustics.
I am working with animal vocalizations recorded at sampling rate of 250000.
Animals are bats, which are known to produce sounds in high frequency.
In…
user305883
- 165
- 9
0
votes
0 answers
understanding quadratic form in proof of positive definiteness of laplacian matrix
Consider the proof at page 2 found here: https://people.orie.cornell.edu/dpw/orie6334/Fall2016/lecture7.pdf
I cant wrap my head around the 2nd and third line:
\begin{align}
&= \sum_{i \in V}x(i)^2 - \sum_{(i, j) \in…
0
votes
0 answers
Derive quadratic form of this laplacian matrix
Lets look at the following laplacian: $L = I - \frac{1}{d}A$ and the graph $H = (U, V)$.
I am trying to derive the known quadratic form of this laplacian $x^T Lx = \frac{1}{d}\sum_{u, v \in H}(x_u - x_v)^2$ but i cant manage to do it.
This is what i…
0
votes
0 answers
Autoencoder on spectral image ASCII data file
I am discovering Autoencoder CNN, I took a look around on tutorials, I see lot's of examples with images as input. I was wondering if it is possible to use files whose pixels are represented by Ascii codes in .txt format ?
For example, a .txt file…
user979974
- 137
- 5