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.

Filter by
Sorted by
Tagged with
0
votes
2answers
23 views

Thematic clustering of text

Please advise on starting points, research (papers,frameworks) related to thematic clustering of text. In particular on a system with two levels of clustering where second level has a temporal nature....
0
votes
0answers
9 views

How to Perform Coordinate Constrained Clustering

Constrained Clustering typically refers to problems where certain pairs need to be included in or excluded from the same cluster. However the problem I'm dealing with has a constraint on where the ...
-1
votes
0answers
12 views

Confused how to apply KMeans Clustering algorithm on my dataset to predict the difficulty level of a course

How can I apply clustering on this dataset to predict the difficulty level of a particular course in this dataset there are many student and each student has opted every course.
1
vote
1answer
16 views

Heterogeneous clustering with text data

I have a dataset which consists of multiple user ratings. Each rating looks similarly to: ...
0
votes
0answers
3 views

Distance Dependent Chinese Restaurant Process v/s LDA for document clustering

I am trying to use Distance Dependent Chinese Restaurant Process (ddCRP) for clustering documents. Specifically, clustering users in a search log (AOL log). Each user is a document with his queries ...
0
votes
0answers
18 views

Identify and correct mislabeled categorical data in supervised learning

I have game/player level football data in 230 dimensions and want to classify the likely position that each player was playing in each match. The data is labelled, however each player is classified ...
1
vote
0answers
16 views

Assigning points to fitted planes

I’m working on a project involving fitting planes to 3D point clouds. The actual plane fitting part is working fine, but I’m trying to decide the best way to actually bound the fitted planes by the ...
0
votes
1answer
16 views

Clustering without information about identifier

I have a data-set with different products and binary value if it was sold in a store or not. I looks like: ...
0
votes
0answers
10 views

Dimension reduction using non-linear PCA

I am working on an undergraduate astronomy research in which we are analyzing geometrical complexities of different sattelite images of man-made and natural structures on Earth. The different images ...
0
votes
1answer
24 views

What is the difference between biclustering and clustering?

After reading the wiki page for biclustering (https://en.m.wikipedia.org/wiki/Biclustering), I am really confused on what is the difference between biclustering and clustering? Any explanation/...
0
votes
1answer
33 views

Binary Classification of a ship Dataset

I want to create a ship detection classifier from a dataset that is formed by 4000 photos(3072*2048).Basically i want to classify the dataset to ship-image and no-ship. I am thinking of 2 solutions- ...
0
votes
0answers
21 views

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 ...
1
vote
1answer
28 views

How to improve results for clustering of words

I have a list of words (names actually) on which I would like to apply some entity resolution. My first guess was to create clusters of similar names so I could extract a representative entity from ...
1
vote
1answer
18 views

Determining number of clusters in high dimensions

I am doing KMeans clustering for sentence embeddings and my problem is the number of clusters. In general, feature size is an order of a few hundreds (in this case 768) and my concern is the sparsity ...
1
vote
0answers
15 views

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 ...
1
vote
0answers
17 views

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 ...
1
vote
1answer
34 views

Clustering after PCA: Use the standardized data, or take into account the variation explained at each PC?

I am interested in clustering daily gridded data. Because of the many dimensions (gridpoints), I first perform PCA to reduce the dimensionality and keep the n-first PCs that account for at least 85% ...
1
vote
0answers
22 views

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 ...
0
votes
1answer
17 views

Clustering a variable based on another variable or set of variables

df11[['COMPONENT_ID','FIRMWARE','SERIAL','CRP0_VDDN']].head() Consider I have these four columns to analyse. I want to form say 3-5 clusters of COMPONENT_IDs with ...
1
vote
1answer
30 views

Clustering with Only Categorical Features

I am trying to do clustering with a bunch (24) of categorical features. I have done some research and found a lot of people recommending something such as K-Modes. I tried running K-Modes on my data ...
0
votes
0answers
16 views

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 ...
1
vote
2answers
21 views

Pre-processing mixed data prior to clustering

I am new to hierarchical clustering, and wish to perform clustering on mixed data. I am slightly confused on the necessary pre-processing steps. I understand how to pre-process purely continuous data, ...
0
votes
1answer
21 views

I want to know which machine learning algorithms can be used for trajectory classifications?

I am working on project for clustering of air objects based on their trajectories. Like I want to train a model on dataset of different flying object's trajectories so later I can predict what type of ...
0
votes
1answer
23 views

Dimensionality reduction without select components

I would like to use dimensionality reduction algorithm in my pipeline. I have 2k features and I'm using xgboost. My model is rebuilding each day (there are new records that should be involve to ...
2
votes
1answer
22 views

Trying to understand the Fowlkes-Mallows Score

I recently bought Chris Albon's ML flashcards and I'm working my way through them. But this one on the Fowlkes-Mallows score has me stumped, as his definitions of false negatives and false positives ...
2
votes
1answer
12 views

Doubt on scope of text classification problem

I have a dataset that describes the sellers who are selling various brands. I need to identify the source (where did he buy those brands he is selling from) of those sellers. (Dimension of dataset 11,...
0
votes
0answers
20 views

How do clustering works in Gravitational Emulation Local Search

I've been reading this paper titled Efficient clustering in collaborative filtering recommender system: Hybrid method based on genetic algorithm and gravitational emulation local search algorithm for ...
-1
votes
0answers
19 views

How to find optimal number of clusters (Statistical Analysis) using Python

I want to find optimal number of cluster in K-Means clustering. We have different methods to find best cluster using Elbow method and avg. silhouette score. But both are descriptive methods, Means we ...
-2
votes
0answers
20 views

Clustering for Mixed Categorical and Numeric Data

My dataset contains three categorical variables and three numerical variables. brand model trim mileage price age honda civic vti oriel 91000 1750000 8 I need to find ...
1
vote
1answer
67 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 ...
2
votes
1answer
141 views

Customer Segmentation and Category association

I have to solve two questions on the following dataset: 1. arrange customers into mutually exclusive groups.explain the clusters. 2.identify 1-1 product category association rules for each cluster, i....
2
votes
2answers
32 views

Which algorithm to use to identify clusters with a similar value?

Here, an example of my problem: 10000 observations of people with several features [age, gender, region, number of sons, ...] and a value to predict "income". There is not a general relationship ...
4
votes
1answer
17 views

Detecting off state in the magnitude of accelerometer data?

I have a univariate time series signal. It's the magnitude of an accelerometer attached to an engine. I need to create an algorithm to detect off state, please see the black lines in the image below....
3
votes
0answers
36 views

What are the data preprocessing steps required before running K-Modes?

I have a clustering task at hand. The data that I have contains only categorical variables. So, k-modes seemed like the best option. But I am not sure what are the data pre processing steps required ...
0
votes
1answer
19 views

Hot Encode vs Binary Encoding for Binary attribute when clustering

I am planning to use data for a clustering problem that contains a column with a binary value BUY/SELL. Should I be converting this attribute and assign it binary values (BUY=1, SELL=0), and keep it ...
0
votes
0answers
25 views

What's the way to categorize user if user can fall into multiple group

Let's assume I have a sample data looks like this ...
0
votes
0answers
13 views

Object detection - noisy world coordinates clustering

I'm performing object detection (2D) via a robot that moves (left-right-left - around 10 seconds for the loop). The robot also has a depth camera and positioning sensors (odometry). Each frame the ...
1
vote
1answer
31 views

implementing an algorithm that mixes data clustering and linear regression

i have the following dataframe available in the link as a csv, it conveys information about stars. more specifically - column ID represents arbitrary ID of sample. column z represents my target ...
1
vote
1answer
20 views

Data discrimination after clustering

My task consists of two points: 1) Make data clustering; 2) Assign new data to the resulting clusters; I wanted to highlight the boundaries of clusters as min/max values ​​for each coordinate of an ...
0
votes
1answer
18 views

Clustering cartesian coordinates associated with 1 categorical feature

I have a series of 2D coordinates X = {x, y}. Each are associated with one categorical variable W that can take 7 different values. E.g: ...
2
votes
1answer
26 views
3
votes
1answer
32 views

Why is hierarchical clustering quadratic and k-means linear?

According to the internet, k-means clustering is linear in the number of data objects i.e. O(n), where n is the number of data objects. The time complexity of most of the hierarchical clustering ...
0
votes
1answer
18 views

Clustering of sparse matrix with many co-variates

I have a 2M x 2000 sparse matrix where rows represent an item and columns represent dimensions. I want to understand whether there are meaningful clusters in the data and I started to explore the ...
4
votes
2answers
76 views

Is there a way to recognize which of these scatter plots is “better”?

I doubt better is the correct adjective, apologies for that. What I mean is this: I have a set of files (1200~) each paired with a scatterplot image. I need to find a way to classify which data files ...
0
votes
2answers
33 views

How to cluster categorical and numerical data in the same dataset?

I have a dataset in which it contains both numerical and categorical data. This can be done using supervised learning algorithms, but I am eager to see how this data can be clustered using some ...
1
vote
0answers
11 views

Clustering algorithms in pre-processing for classification problem

Through experience it was found that using k-means does not give accurate results to use them in pre-processing of classification, so if I use another clustering algorithm, can results be more ...
2
votes
0answers
17 views

Visualizing the difference of a set of strings

I have a distance metric on a collection of strings on the order of tens of thousands. What would be an intuitive way to summarize how 'different' these strings are or when they overlap? My goal is ...
1
vote
0answers
9 views

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. ...
-1
votes
2answers
57 views

Clustering data set with multiple dimensions

I have a data set which is similar to the following: It is recipe data along with the composition of the recipe (in %) I have 91 recipes and 40 ingredients in total. I want to be able to cluster ...
0
votes
2answers
66 views

K-Means Clustering for data points with multiple attributes

I'm very new to K-Means clustering. Every example that I have seen has a two-dimensional data set. I am working to classify recipes of varying ingredient composition into families. Each recipe is ...

1
2 3 4 5
19