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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T-SNE good clustering but SVM classification poor
I am trying to classify in 4 different classes, paragraph embedding vector computed with doc2vec using an non-linear svm over them.
When I visualize the embeddings using tensorboard t-sne I can see ...
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Item position in Gravity Search Algorithm
According to this article titled Efficient clustering in collaborative filtering recommender system: Hybrid method based on genetic algorithm and gravitational emulation local search algorithm
This ...
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Average n 2D clusters into one finale result
I have n clusters run on 3D data, resulting n 2D clusters, I couldn't run the clustering model on a one year satellite mages time-serie. So I did chunks of one month and run clustering which finally ...
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End to end k-means clustering - python
i'd like to share with you my path in a clustering exercise (via K-means using python), in order to understand if i made some errors or if there is something more that can i do.
General Overview
My ...
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Clustering a dataset and creating a model per each cluster
I was wondering if it makes sense to cluster a dataset to find closely related data points and train a binary classification model for each of this clusters as they would be minidatasets. I'll ...
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Clustering and producing final results to find next best customer to target(Ranked)
I have a problem where I need to cluster customer data that has all possible attributes to identify the next potential customer who can succeed the last customer in terms of buying a certain product. ...
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Coding a Content Addressable Memory on a GPU
I´m trying to code a CAM or more simply a dictionary storing the pointer of the data accessible by a key. I try to do it with a GPU but all attempts have been inefficient compared on using System....
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which algorithm used by sklearn.model_selection.StratifiedShuffleSplit for clustering into n_splits
which algorithm is used by sklearn class StratifiedShuffleSplit for clustering/stratification into n_split. dendrogram looks evident but can anyone suggest any reference.
class sklearn....
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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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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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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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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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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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Clustering data with a constraint
I am trying to find a way to cluster/group students by their knowledge of different subjects.
Given following as an example:
...
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How to structure my data into features and targets for PCA on Big Data?
I want to apply the PCA algorithm from Scikit-Learn.(https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html ) At the part where I have to separate the features and the ...
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How can I adjust the legend when visualizing clusters in two dimensions?
How can I change the legend as we can see now the legend has some cluster numbers missing. How can I adjust the legend so that it can show all the cluster numbers (such as Cluster 1, Cluster 2 etc, no ...
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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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Find all recurring subgraphs/patterns of maximal size in a single undirected, labeled, connected graph
I would like to identify all subgraphs of maximal size (maximum number of nodes) that are recurrent in a single undirected, labeled, connected graph. I provide exemples of input and expected output ...
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I have 32k black and white images. Want to do clustering on them
As the title says I'm trying to do clustering on a set of black and white images. These images are all 200x200 with black dots on a white canvas Example pics here (These are not actual photos from the ...
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Different approaches for categorical non-ordered data clustering in R
I'm trying to find different clustering approaches for only categorical data in R, so far I found:
klaR for kmode
cba for rock
Hierarchical clustering (agglomerative or divisive) with a categorical ...
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ML Approach for Getting List of Observations with Similar Features (Discrete+Continuous)
I have a dataset with 19k observations. Each has approximately 448 features:
- Text description turned into vectors of size 300
- 16 categorical variables represented numerically
- The remainder ...
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Clustering a set of vectors
Provided a set ($m$ no. of) of n-dimensional vectors what would be the correct unsupervised approach to cluster them? The vectors essentially represent patterns.
For example:
Set of vector is ...
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How to find vertical clusters in 1-D data
I have residuals of a multivariate time series data obtained from sensors on a server.spikes in the plots of residuals indicate abnormal server state. I want to cluster the data into vertical clusters ...
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Can I use entropy as a measure for determining significant variables in a cluster after clustering?
After clustering my data into k groups, I would like to determine for each of the clusters, which dimensions(variables) significantly describe that particular cluster. For example, lets say cluster A ...
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How to validate clusters after calculating Gower distances and Ward's clustering in R
I am trying to apply Ward's clustering on a mixed types dataset, and wanna explain what I did (maybe helpful to others), and I have some questions regarding this analysis, mainly how to validate my ...
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Clustering of multi-label data
The dataset consists of
1) a set of objects and
2) a set of labels, which are used to describe the objects.
For the moment, for simplicity sake, each label can be marked as either true or false (...
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Are there any public datasets about mental health of patients containing physiological and psychological symptoms?
I would like to segment mental illnesses with clustering using machine learning. To do so I need training dataset which contains physiological and psychological symptoms of an subject. The closest ...
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Clustering and graphing similarities of sentence subjects
I have a bunch of sentences. Each sentence is given a weight of how "close" it is to a particular subject.
Ex. "I love reading math books" Subjects for the above sentence = ...
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Anomaly detection in structured textual data
Pls refer screenshot for sample data. As can be seen most of the fields in data are textual and highly correlated but each row has unique values and hence won't be right to call it categorical. I ...
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recommend new category paths based on factor item matrix and sales of the items
Matrix A be a user item matrix. Upon performing UV decomposition, I have just the V matrix.
The matrix A differs every week and I get a new V matrix every week. The matrix U is not kept track of and ...
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What is the best to identify the proper hierarchy of this data?
So I worked on a hierarchical clustering algorithm to be able to determine which items are most similar, and what attributes are most important. I have two tables:
Table 1: contains a bunch of item ...
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Is there a clustering algorithm that can cluster time series dataset based on variation ratio (or quantity)?
I am learning machine learning from scikit-learn and reading its docs.
Clustering clusters groups based on the Euclidean distance and filters them by different ways ex: Gaussian distribution, or mean-...
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Assigning a new document to a cluster based on keywords extracted and tf-idf
I have about 40 clusters of documents defined by a combination of k-means clustering algorithm and hand curation. For example, some of the clusters given by k-means are too noisy so they have been ...
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Preserving labels in latent space clustering
I generated a latent space from a VAE model for my dataset which consists of images depicting different font styles. The objective is to reduce the dimensionality of this latent space in order to ...
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Recommender system that connect users with each other , should I go for content based or collaborative filtering?
I am trying to build a system where user come on the platform and he chooses a topic(predefined few topics) and then we connect him with any random online user who chooses the same topic. Then they ...
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Code or Package to cluster sequences (or time series) of different lengths based on HMM?
Is there any existing code or packages in Python, R, Java, Matlab, or Scala that implements the sequence clustering algorithms in any of the following 2 papers?
1) 'Clustering Sequences with Hidden ...
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Time-series clustering Quality Measures
I am clustering time-series datasets which are not labeled (No Ground truth) and I want to measure the quality of the clusters.
Could you please suggest any Clustering performance evaluation methods ...
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Applicable method for the clustering of time-series consisting of multiple events
I'm currently dealing with a time-series clustering problem at work and I need help with picking/suggesting the right methodology. The problem is similar to clustering of users on a website based on ...
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Autoencoder ambivalent about order of input data?
The problem I'm working to solve is this:
Given a musician's prerecorded free-form playing. I want to analyze each of the individual notes to determine how "in-rhythm" it is. See the graph in the ...
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Grouping/clustering similar words python
I have a question regarding grouping of similar words for example I have list of words give below:
artificialintelligence
Artificial Intelligence
AI
Machine Learning
ML
Data Analytics
Data & ...
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Classifying variable types on a list of variables
I have a list of around 700 variables which I need to perform a variable cleanup on. What complicates things is there are different numeric codes which flag an invalid value and these differ by the ...
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What is the difference between K-Means & Self Organized Maps?
It seems they both perform clustering. They both reduce the dimensionality of the input data and classify further inputs based upon their distance/similarity to the center points. These points then ...
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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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Limitations while using orange for clustering
I have tried clustering using kmeans in Orange but it looks like there are certain limitations as listed below,
- Supports up to 5000 records only
- no. of clusters can be only 30
Can someone please ...
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Clustering/ Classifying users based on sequence of action and time
I have some user data where each user has a certain pattern of being at different places for some time. I would like to create a model which will cluster/classify these users based on these patterns ...
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How do I simultaneously select multiple values for k-means in WEKA?
I have tried WEKA's Experimenter. However, it's for classification.
I'm looking for a way to apply the k-means algorithm on the same dataset but with multiple 'k' values. Is there any option in WEKA'...
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Find words related to high or low score
I am working on text analysis problem.
Person X can log in his goals and his actions to achieve his goal. Also their score is calculated based on some formula to measure progress of the goal.
For ...
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Conceptual clustering with sklearn?
How can I perform conceptual clustering in sklearn? My use case is that I have English Wikipedia articles that I'm doing unsupervised learning on (tfidf -> truncated svd -> l2 normalize), and I'd like ...
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KDE on TF-IDF - sensitive bandwidth
I am clustering text based on TF-IDF features and DBSCAN (density based), and trying to rank points based on their 'belonging' to the cluster. Since my clustering is density based and my points can ...
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PCA Reduction resulted in an elliptical form
I have a dataset with 19 features (columns). I normalized them using sklearn.preprocessing.normalize then I used PCA to reduce them to 2 components for plotting ...
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