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Clustering

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**Clustering**

What is Clustering?

Clustering is a data mining technique used to group similar data points together into clusters. The goal is to discover inherent groupings in the data, where data points within a cluster are more similar to each other than to those in other clusters. It is commonly used for data analysis, pattern recognition, image analysis, and anomaly detection. Common clustering algorithms include k-means, hierarchical clustering, and DBSCAN.

Find 3.1k organizations using Clustering on Sumble →

What other technologies are related to Clustering?

Clustering Competitor Technologies

Regression
Regression is a supervised learning technique, used for prediction instead of grouping data like clustering.
classification
Classification is a supervised learning technique focused on categorizing data points, unlike clustering which groups data based on similarity.
decision trees
Decision trees are a supervised learning method used for both classification and regression, not directly related to the unsupervised nature of clustering.
decision tree learning
Decision tree learning is a supervised learning paradigm, thus a competitor to clustering.
neural networks
Neural networks are often used for supervised learning tasks (classification, regression) and can be used for dimensionality reduction (autoencoders) and can be used for clustering by using the latent representation as input to another algorithm.
regression techniques
No summary available
Regression is focused on predicting a continuous output variable, contrasting with clustering's goal of grouping similar data points.
Random Forests
Random Forests is a supervised learning algorithm, used for classification and regression, not clustering.
Random Forest
Random Forest is a supervised learning algorithm, used for classification and regression, not clustering.
Number of organizations that mention technology
3,069
Clustering
1,429
Regression
1,311
classification
1,136
decision trees
110
decision tree learning
2,931
neural networks
29
regression techniques
673
Random Forests
1,677
Random Forest
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Clustering Complementary Technologies

dimensionality reduction
Dimensionality reduction techniques (e.g., PCA, t-SNE) can be used to preprocess data before clustering to improve the quality of clusters.
Number of organizations that mention technology
3,069
Clustering
158
dimensionality reduction
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Which job functions commonly mention Clustering?

Data Scientist
0.9% of all Data Scientist jobs mention Clustering
View 2.2k jobs on Sumble
Database Administrator
0.7% of all Database Administrator jobs mention Clustering
View 148 jobs on Sumble
Machine Learning
0.4% of all Machine Learning jobs mention Clustering
View 375 jobs on Sumble
AI Engineer
0.3% of all AI Engineer jobs mention Clustering
View 235 jobs on Sumble
Data, Analytics & Machine Learning
0.2% of all Data, Analytics & Machine Learning jobs mention Clustering
View 3.2k jobs on Sumble
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Which organizations are mentioning Clustering?

Clustering
JPMorgan Chase
Finance and Insurance 
45 team
mention Clustering
↗
 57 people
use Clustering
↗
Clustering
Amazon
Retail Trade 
33 team
mention Clustering
↗
 83 people
use Clustering
↗
Clustering
Visa
Finance and Insurance 
29 team
mention Clustering
↗
 12 people
use Clustering
↗
Clustering
Wells Fargo
Finance and Insurance 
25 team
mention Clustering
↗
 32 people
use Clustering
↗
Clustering
Deloitte
Professional Services 
23 team
mention Clustering
↗
 54 people
use Clustering
↗
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