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Questions tagged [optics-algorithm]

Ordering points to identify the clustering structure (OPTICS) is an algorithm for finding density-based clusters in spatial data. [from Wikipedia on OPTICS]

"Ordering points to identify the clustering structure (OPTICS) is an algorithm for finding density-based clusters in spatial data."

[Wikipedia on OPTICS]

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Python Implementation of OPTICS (Clustering) Algorithm

I'm looking for a decent implementation of the OPTICS algorithm in Python. I will use it to form density-based clusters of points ((x,y) pairs). I'm looking for something that takes in (x,y) pairs and outputs a list of clusters, where each cluster…
Murat Derya Özen
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ELKI OPTICSXi - how set xi?

I'm trying to use ELKI to cluster a dataset of geolocations using OPTICS. I've understood that to extract the clusters, I need to use the OPTICSXi algorithm rather than OPTICS which computes just the clusters order. I was wondering if you could give…
Deborah
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ELKI implementation of OPTICS clustering algorithm detects only one cluster

I'm having issue with using OPTICS implementation in ELKI environment. I have used the same data for DBSCAN implementation and it worked like a charm. Probably I'm missing something with parameters but I can't figure it out, everything seems to be…
Ilya Khaustov
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OPTICS Clustering algorithm. How to get the best epsilon

I am implementing a project which needs to cluster geographical points. OPTICS algorithm seems to be a very nice solution. It needs just 2 parameters as input(MinPts and Epsilon), which are, respectively, the minimum number of points needed to…
smellyarmpits
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interpreting the results of OPTICSxi Clustering

I am interested in detecting clusters in areas with varying-density, such as user-generated data in cities, and for that I adopted the OPTICS algorithm. Unlike DBSCAN, the OPTICS algorithm does not produce a strict cluster partition, but an…
doublebyte
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How to extract clusters using OPTICS ( R package - dbscan , or alternatives )

This might be a mix of a R question and an algorithm question. The question is about both OPTICS in general and the R implementation of optics in the package "dbscan" ( https://cran.r-project.org/web/packages/dbscan/dbscan.pdf ) My main reason to…
ednaMode
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Changing value of a 2D array element changes the complete column

When I print my arr value i get the correct values for my 2D array but when I exit the while loop my values are all wrong. I am not sure what i am doing wrong. #num runs n = 4 x = np.linspace(-1,1,n) y = np.linspace(-1,1,n) …
Rodrigo Rivas
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OPTICS parallelism

I have the following script (optics.py) to estimate clustering with precomuted distances: from sklearn.cluster import OPTICS import numpy as np distances = np.load(r'distances.npy') clust = OPTICS(metric='precomputed', n_jobs=-1) clust =…
dzieciou
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Obtaining cluster boundaries of ELKI OPTICSXi

I have a one-dimensional data set for which the histogram plot shows multiple local maxima, so I know that there are multiple regions in my one-dimensional space where the data is more dense. I want to determing boundaries for these dense regions…
Niek Tax
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Priority Queue in R for OPTICS implementation

I need to construct a priority queue in R where i will put the ordered seed objects (or the index of the objects) for the OPTICS clustering algorithm. One possibility is to implement it with heap with the array representation, and pass the heap…
phoxis
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sklearn OPTICS and precomputed cosine matrix yields no clusters

i am trying to use sklearn.cluster.OPTICS to cluster an already computed similarity (distance) matrix filled with normalized cosine distances (0.0 to 1.0) but no matter what i give in max_eps and eps i don't get any clusters out. Later on i would…
Johannes valbjørn
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Difference Between OPTICS and HDBSCAN clustering techniques

As a part of my assignment, I have to work on both HDBSCAN and OPTICS clustering technique. I have researched on many sites to identify the difference between these algorithms. All I got was OPTICS algorithm is a slight variation from HDBSCAN. I…
Minu
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I am having a hard time understanding the concept of Ordering in OPTICS Clustering algorithm

I am having a hard time understanding the concept of Ordering in OPTICS Clustering algorithm. I Would be grateful if someone gives a logical and intuitive explanation of the ordering and also explain what res$order does in the following code and…
Omar Rafique
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DBSCAN vs OPTICS for Automatic Clustering

I know that DBSCAN requires two parameters (minPts and Eps). However, I am confused on what parameters are needed for OPTICS because some sources say it requires eps while others say it only requires minPts. Which algorithm would be the better to…
user3315340
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ELKI OPTICS pre-computed distance matrix

I can't seem to get this algorithm to work on my dataset, so I took a very small subset of my data and tried to get it to work, but that didn't work either. I want to input a precomputed distance matrix into ELKI, and then have it find the…
Froblinkin
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