Questions tagged [clustering]

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval etc.

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k-means with soft constraints (KSC) algorithm: how to minimize objective function?

I'm learning about the KSC algorithm as described in "Clustering with Missing Values: No Imputation Required" by Kiri Wagstaff. Here's a small dataset to use as an example: ...
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How to calculate performance and change train and test data size in MATLAB NNC Toolbox?

I used MATLAB Application toolbox for clustering but I don't know how to : Calculate performance and Error rate How to change test and train data size Script: ...
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Remove noise by clustering on which step of pre-processing is better?

I am working on a classification task. The dataset is a UCI data set about machine learning with 200 observations and 2 classes. Part of my model includes the following preprocessing steps: remove ...
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How can I improve the results of my clustering

I am working on a project with the idea to cluster the sound waves of key strokes on a computer. So far what I have done was recorded about 50 keystrokes per key (only have done 1 - 10 so far), found ...
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What is an appropriate statistical method for determining correlations between variables with likert scale data?

I am conducting an exploratory analysis with a dataset of about 200 records (all likert scales (numeric)). I aim to determine the correlations between the different variables that the responses ...
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35 views

Feature transformation possible at selected features or only at all?

I want to cluster. I have different features for that. Some features have a very small value range (from 0 to 0.8) and some have a very large value range (from 0 to 5 million). I want to use the ...
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42 views

Evaluate clustering by using decision tree unsupervised learning

I am trying to evaluate some clustering results that a company did for some data but they used an evaluation method for clustering that i have never seen before. So i would like to ask your opinion ...
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Labels are not given for multiclass classification problem

I have probably a weird question. If you are dealing with a multiclass classification problem, do you always have already determined target output/labels? I have e.g. a huge data set with a lot of ...
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K-Means initialization

K-Means initializes the centroids randomly, but there are other methods to initialize. In this paper, http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf, they propose randomly choosing a data point ...
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will k-means clustering converge to the same results given the same data set?

I did some study on the k-means clustering algorithm. It seems that the only non-deterministic part is the centroid - initialization. Assume I have 10k data points, and a given k. I then initialize ...
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how to handle outliers for clustering algorithms?

I am wondering what's the best way to handle outliers when using non-supervised clustering algorithms? Thanks!
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Aggregate categorical feature by the target

Having a list of triplets {X1,X2,Y} such as : {pennsylvania, fever , malaria} {pennsylvania, headache , malaria} {arizona, ketone smell , flu} {new york, fever , cancer} {ohio, hand pain , ...
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Reduce drug spend using medical claims analytics

I have access to medical claims data from a US health insurance company. I believe there's an opportunity to find some cost savings by switching the site of service from high cost outpatient ...
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Categorial Encoding with different cardinality

I have some user data for his data activities. Some examples of the columns are : Activity : ex. youtbube , viber, whatsapp etc etc. Cardinality > 1000 Region : Area identifier Cardinality > 10000 ...
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Tuning parameters in Affinity Propagation

I am doing Affinity Propagation clustering and trying to do tuning, but it takes time. A lot of time actually. As I am beginner I do not know how to get clusters. I need cluster numbers from 1 to 20 ...
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Clustering categorical variable values based on continuous target values [closed]

Let's say I have $n$ data points with just one categorical feature $x$ and a continuous target variable $y$. I want to divide the possible values of $x$ into subsets such that the value of $y$ doesn't ...
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Customer Segmentation: Should I use a variable, representing a product, that is unpopular in the dataset for K-Means Clustering?

I am working with a data set that, besides customer age and income, tells the balance a customer has in different type of bank accounts: Checking, Shares, Investment, Savings, Deposit, Mortgage, Loan, ...
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Clearest way to visualise temporal data?

I've collected bus arrival times at my local bus stop from the past month - so I have every time my bus (a specific bus number) shows up at my bus stop for each day of the week (Monday, Tuesday, etc.)....
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Testing if a sample fits into an existing cluster

I have a sample of data I'd like to create a model from, which would create N clusters. After the fitting to clusters, I'd like to test various samples against the existing clusters, seeing if the ...
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Detect geolocation match a GeoJson pattern

I'm trying to detect if a geolocation (lat, lng) match a GeoJson pattern. As example i have line of location points and i want to detect if a new point can match that pattern in certain radius, like ...
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Looking for similar items in a large data set

I have a large database of people and I want to show a small number of people who are similar to each person in the database. So if one of the people was Wolfgang Mozart I would want to show Beethoven,...
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Clustering data using KMeans centroids of base period for pattern analysis

I have a data frame consisting of 12 months of Customer Transaction Level Data. The data is unsupervised. The data is divided into 6 sets of 2 months period each. Taking first period as the base, I am ...
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customer segmentation with unbalanced data

I am trying to do a customer segmentation on my transactional data and I am struggling a little bit on the best approach. Since it is an unsupervised model I can throw it to any algorithm and get some ...
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1answer
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Efficient algorithm to find the lowest value cluster in a series of values

Let's say I have a list of numeric values that tend to be grouped into some number of clusters of values that are close to one another. I'm aware of things like k-means to group these into groups of ...
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Recommendation needed for unsupervised clustering on mixed data task

I have a task to perform unsupervised cluster analysis on mixed datatypes: images, physical and business measures – continuous and categorical. Businesswise: there are images of products and ...
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How to treat column with potentially meaningful NaNs

My data set has a column that indicates the time taken (in days) for members on a site - each with an ID - to sign up for an event. This can range between 1 to 300 days, with about half of the rows ...
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Method for 'Simple' Clustering?

In a recent adult education class I took the prof shared a spreadsheet that was written in VBA code and takes ages to execute, I'm sure ...
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hierarchical clustering doesn't work as expected

I have a precomputed distance matrix. I'm trying to do an hierarchical clustering using scipy: ...
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How do you Show a Difference between Two Groups (Clustering)

I am approaching a data problem. My data set consists of observations of (X,Y) coordinates indicating a position on some grid. There are two groups based on a variable Z. Group A is all the points ...
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Choosing a distance metric and a clustering algorithm for time series

For every entity I have a corresponding time series which is built by a sliding window (win_size=7d, win_shift=3d, so we have overlapped windows) With every win-shift, we count how many users are ...
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Cluster evolution over time

I have a dataset of transactional data with customer ID and I want to segment the dataset into groups using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
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Rank links from rss feed

I am trying to create a script to filter the most "intersting" articles from an rss feed and rank them. ...
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How to plot datasets 1 factors for K mean clustering python

I'm unable to plot the data for K mean clusering algo usingsklearn as it throws this error : TypeError: scatter() missing 1 required positional argument: 'y' Here is the function I have written to ...
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Apply a clustering algorithm on categorical data with features of multiple values [duplicate]

Let us I have a people data like gender, age, marital status, education, employment, hobbies. I want to make clusters of those people, having some similarity/common among them (for example they have ...
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93 views

Question about Similarity vs Dissimilarity Matrix

Right now, I'm working on a coming up with a similarity vs dissimilarity matrix for a set of data points for a clustering algorithm. My question is, if I want to use one of the many clustering ...
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Question About Coming Up With Own Function for Distance Matrix (For Clustering)

Right now, I am currently working on implementing a clustering algorithm with millions data entries with regards to game users for a mobile game. A lot of the features I plan on using are unique to ...
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Scaling of ordinal data before both hierarchical and KMeans clustering

I am new to data analytics. As part of my assignment I have to perform both hierarchical and Kmeans clustering on a data set wherein all applicable variables are ordinal (1-5 rating scale). Do I need ...
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Clustering in python when imbalanced data sets exist

I have a set of measurements with four features. Two features are continuous (time and distance) and two are discrete. We also know that the population consists of two groups. One is the minority ...
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How to tune / choose the preference parameter of AffinityPropagation?

I have large dictionary of "pairwise similarity matrixes" that would look like the following: similarity['group1']: ...
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1answer
28 views

Clustering stores based on weekly data

I have 1 year transaction level data aggregated at a weekly level for 1000 different stores. I want to cluster similar stores based on 8 variables such as sales, customer count etc. The concern is ...
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Setting up Zeppelin to work with a Spark Cluster

I have made a spark cluster containing 2 workers and 1 master. I followed the following link to set up the spark clusters. After successfully setting up the spark clusters I wanted to connect it to ...
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what arguments should I pass to dbscan or optic in order to divid the data in a specific way

I have thousands of very similar data set 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 eps and minPoints and even ...
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Is there a machine learning method to rank customers credibilty (goodness of a customer)?

I am working on a machine learning project that I want to rank each customer and put on a scale smt like one of those https://cdn1.vectorstock.com/i/1000x1000/90/40/credit-score-indicators-with-color-...
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3answers
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Supervised clustering

I'm working on a clustering problem. I have a training set composed of sets of points where the clusters are known and I want to find the good clusters on a testing dataset. It's a kind of supervised ...
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1answer
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How to validate a clustering model without a ground truth?

Im dealing with a dataset (text messages about source code comments) that are not labeled. I don't have a assumption about the implicits classes in this dataset. I want to discovery (by clustering) ...
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2answers
33 views

Categorical features preprocessing for clustering

Can anyone tell suggest the best practice for clustering data with mixtured features (both with categorical and continuous). I am struggling with a problem; I realized that for all metrics algorithms ...
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Clustering of very high dimensional data and large number of examples without losing info in dimensions

I'm trying to get a grasp on scalability of clustering algorithms, and have a toy example in mind. Let's say I have around a million or so songs from $50$ genres. Each song has characteristics - some ...
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How to remove noise using morphological filtering

I have two groups of dots that both contain noise between them: The line that separates the two groups in the picture is diagonal in shape. I tried to use morphological filtering on this image to ...
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How to calculate Fuzzy C-Means problem by hand

I figured that this doubt next can interest another students like me and help others also that are trying to understand mathematically the fuzzy c-means mathematical mechanism already that some books ...
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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. ...