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DBSCAN means density-based spatial clustering of applications with noise and is a popular density-based cluster analysis algorithm.

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Looking for spatial clusters and anomalies. Is DBSCAN the right tool?

I have a regular 2D grid of data points (X, Y) with each point having a value. I'd like to identify clusters and then anomalies that don't belong to those clusters. I'm trying to understand the best ...
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41 views

Shall I use ordinal encoding or One-Hot-Encoding when using DBSCAN for content clustering on websites?

I want to cluster the preparation steps on cooking recipes websites in one cluster so I can distinguish them from the rest of the website. To achieve this I extracted for each text node of the website ...
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DBSCAN - Best way to find the Eps and MinPts for geospatial data (coordinates)

Question: The best way to find out the Eps and MinPts parameters for DBSCAN algorithm? Problem: The goal is to find the locations (clusters) based on coordinates (input data). The algorithm calculates ...
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43 views

DBSCAN Clustering

I used K-means to get the number of clusters for my data(Elbow Method). Then I was trying to see if for some specific hyperparameters can we get the same number of clusters for DBSCAN. I tried Brute-...
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How may I may fit the cluster number while it is going to the outside of the X-axis and when visualizing clusters in two dimensions?

I am writing code for DBSCAN clustering. I find the eps value which is 0.12 with the help of ...
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Good real dataset for comparing Tarjan and DBSCAN?

One method of determining "clusters" in a directed graph is Tarjan's algorithm, which finds all strongly connected components. Given a set of points in some space, equipped with a distance function, ...
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250 views

Nice real data sets for testing DBSCAN?

I'm looking for real datasets on which I could test my DBSCAN algorithm implementation, that is, a dataset of points in (ideally 2 dimmensional) space, or a set of nodes and info about the distances ...
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18 views

Types of artificial anomalies

I am working on some algorithms for anomaly detection The dataset is clean our anomalies so I want to add some artificial anomalies. I have added some anomalies. I get the maximum value of the ...
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28 views

Classifier for DBSCAN [closed]

I have written a code that uses DBSCAN and tries to find the most appropriate eps for my dataset, trying to include most of the data inside a cluster. The problem is that DBSCAN is not a classifier ...
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1answer
846 views

How to use Cosine Distance matrix for Clustering algorithms like mean-shift, DBSCAN, and optics?

I am trying to compare different clustering algorithms for my text data. I first calculated the tf-idf matrix and used it for the cosine distance matrix (cosine similarity). Then I used this distance ...
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33 views

Estimating minPts in DBSCAN for document layout clustering

I am trying to choose parameters for DBSCAN clustering algorithm, in particular minPts. The Wikipedia article suggests a rule of thumb to derive minPts from the number of dimensions D in the data set....
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37 views

Plots of data using DBSCAN algorithm not making sense

I am using clustering for my data. Since the DBSCAN algorithm will also tell me an estimate of clusters that I can use, I have used DBSCAN. I have tried for the ...
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64 views

Clustering Small Text Descriptions

Im presented with a unique text classification problem. Im given a list of descriptions each containing 3-8 words. I know that there are some descriptions that are nearly the same, but the majority ...
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52 views

what arguments should I pass to dbscan or optic in order to divide the data in a specific way

I have thousands of very similar datasets that needs to be divided in diagonal way to two groups. for example: and I tried to play with the argument of dbscan and optic as epsilon and minPoints and ...
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56 views

Is it safe to use labels created from unsupervised model to train a supervised model using the same data?

I have a dataset where I have to detect anomalies. Now, I use a subset of the data(let's call that subset A) and apply the DBSCAN algorithm to detect anomalies on set A.Once the anomalies are detected,...
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207 views

The actual results and results from pickle files are not matching in pandas for DBSCAN clustering

I've built a DBSCAN clustering model. The output result and the result after using the pickle files are not matching. Based on HD and MC column, I am clustering WT column. ...
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1answer
66 views

T-DBSCAN - Implementing STOP logic

I am attempting to implement the T-DBSCAN algorithm described in T-DBSCAN: A Spatiotemporal Density Clustering for GPS Trajectory Segmentation. I have been able to implement most of the logic between ...
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24 views

Are DBSCAN and dbscan from the sklearn.cluster package different?

I'm new to DBSCAN. I was looking at a few examples online and came across a few instances where the following lines were used while importing the dbscan module: <...
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587 views

How to properly use approximate_predict() with HDBSCAN clusterer for text clustering (NLP)?

I have approached text clustering using HDBSCAN based on this article which describes how to do this in R. I've re-written this in Python using this library. The approach is to first calculate TF-IDF ...
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31 views

DBSCAN: How does a quantile of kNN relate to the share core points?

I read this answer by Anony-Mousse to an other question related to density based clustering and how to potentially come up with an eps. It states, that if you want 90% of you points to be core points, ...
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428 views

DBSCAN clustering on document [updated]?

I am new in topic modeling and text clustering domain and I am trying to learn more. I would like to use the DBSCAN to cluster the text data. There are many posts and sources on how to implement the ...
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123 views

Clustering based on geolocation pair

I am trying to process a large set of location data where a list of start and end coordinate is given. For example, ...
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47 views

How to find anomalies/outliers in Panel Data?

I have panel data based on 900000 different entities with 384 time steps and the data is not normally distributed. I am looking for outliers/anomalies, this is unsupervised as I have no examples of ...
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1answer
75 views

Preparing dataframe to carry k-means clustering [closed]

Im trying to apply 3 different algorithms of clustering on my dataset. to check which one fits the best. I'm confused how should I convert my dataframe -k-means -DBSCAN -hierarchical clustering ...
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7k views

KMeans vs. DBSCAN

I am trying to understand some basic clustering techniques. What is the main difference between KMeans and DBSCAN? Can we use both techniques for the same problem?
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How do we interpret the outputs of DBSCAN clustering?

I am starting to learn DBSCAN for clustering but the interpretation part of it seems to be tricky to understand. ...
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32 views

Measure of variety within list/cluster

I have a dataset of about 53000 points. It has been clustered twice, based on two sets of unrelated attributes. For the first clustering (clustering 1) I used DBScan, and it ended up with about 700 ...
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305 views

How do I right feature selection for DBSCAN?

I want to use DBSCAN to recognize any clusters within all text elements from the DOM tree of any webpage. For example all menu items shall be clustered separatey to all main content or footer elements....
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136 views

Clustering 1-d array with constraints?

I have following kind of 1-d array data to cluster with a few constraints: The array has length from 50 to 300, floating, some of them close to 0 and some far away. Goal: divide the array into n ...
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1answer
73 views

Is there an oriented clustering algorithm?

I'm looking for a clustering algorithm that will make cluster depending on a orientation. The DBSCAN algorithm cluster points based on a constant radius : https://upload.wikimedia.org/wikipedia/...
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160 views

Clustering events in a sequence.

I've a sequence of recurring events I want to group together into representing different operation activities of the underlying process. 1) These events might potentially have an order in their ...
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481 views

Is my data good for (DBSCAN) clustering?

I have a particular dataset consisting of 50k elements with 40 features each. I want to try to cluster the data as it is, without any dimensionality reduction. The main algorithm I am considering is ...
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1answer
831 views

DBSCAN - Space complexity of O(n)?

According to Wikipedia, "the distance matrix of size $\frac{(n^2-n)}{2}$ can be materialized to avoid distance recomputations, but this needs $O(n^2)$ memory, whereas a non-matrix based implementation ...
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1k views

What is slowing down classic DBSCAN algorithm

How to apply CSR Matrix on DBSCAN algorithm in python without using any libraries? Update: Matrix size (8580, 126356) I have given a shot and implemented the algorithm. It runs rather slow. I guess ...
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121 views

Clustering of variants of similar news articles

We have data of several news sites, having quite literally millions of entries. As each news site publishes their own version of the news (also each news site may publish several different version of ...
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1answer
6k views

Python clustering and labels

i'm currently experimenting with scikit and the DBSCAN algorithm. And i'm wondering how to combine the data with the labels to write them into a new file. I'd also like to understand how the labels ...
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1answer
45 views

How to select the second point where derivative is greater than 1 in r? [closed]

I'm looking for the exact value of epsilon to run the DBSCAN clustering algorithm. Here's the KNN distance plot. This chart ...
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43 views

Testing unsupervised clustering

Assume we train a KMeans model using data X. This will give a set of centroids that can be used to cluster data X* using a Nearest Centroid Classifier. If we use a density-based model such as DBSCAN ...
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601 views

Scaling DBSCAN clustering - minHash?

Applying density based clustering (DBSCAN) on $50k$ data points and about $2k$-$4k$ features, I achieve the desired results. However, scaling this to $10$ million data points requires a creatively ...
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225 views

Clustering documents - how to evaluate results?

I'm using DBSCAN clustering on a set of documents. The documents' content was converted to TF-IDF matrix, and I'd like to find consistent ways to evaluate the clusters when no added information is ...
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3answers
2k views

Can you l2 normalize word2vec vectors for density clustering?

I have a situation where I have to cluster word2vec vectors (200 length dimension vectors on a very large corpus). I decided to use Density based clustering (DBSCAN, HDBSCAN) because my dataset is ...
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1answer
4k views

How to use precomputed distance matrix and min_sample for DBSCAN clustering method?

I want to perform DBSCAN on my datapoints, but I don't have access to the data, I just have the pairwise distance of datapoints. Additionally, I have no idea about the number of clusters but I do want ...
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393 views

Which Clustering algorithm to use for unique 4Dimension dataset before feeding to correlation?

Lets give an example X: 1 2 3 4 5 Y: .9 .91 .92 .93 .94 Z: 20 36 999 211 M. 4000 3456 1 0 When I have such dataset, Which clustering algorithm to choose ? Also, ...
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1answer
209 views

How to Interpret the output of PCA?

I have dataset of 50000 values (rows) and 1000 variables (columns). Since this is high dimensional, I am unable to work with just DBSCAN. So I am trying to use PCA (principle component analysis). ...
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154 views

Clustering with restrictions - Silhouette and C index metrics

I am working on clustering with DBSCAN but with a certain constraint: the points inside a cluster have to be not only near in a Euclidean distance way but also near in a geographic distance way. It is ...
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16k views

Knn distance plot for determining eps of DBSCAN

I would like to use the knn distance plot to be able to figure out which eps value should I choose for the DBSCAN algorithm. Based on this page: The idea is to calculate, the average of the ...
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1answer
13k views

How to plot/visualize clusters in scikit-learn (sklearn)?

I have done some clustering and I would like to visualize the results. Here is the function I have written to plot my clusters: ...
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735 views

How are clusters from DBSCAN sometimes non-convex?

I've been using clustering in my bag of ML techniques for quite some time now, and I've never found a satisfying answer to this question. In DBSCAN, we define a maximum radius with which to form ...
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986 views

Clustering pair-wise distance dataset

I have generated a dataset of pairwise distances as follows: id_1 id_2 dist_12 id_2 id_3 dist_23 I want to cluster this data so as to identify the pattern. I ...