Cluster analysis | Data mining
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) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-objective optimization problem. The appropriate clustering algorithm and parameter settings (including parameters such as the distance function to use, a density threshold or the number of expected clusters) depend on the individual data set and intended use of the results. Cluster analysis as such is not an automatic task, but an iterative process of knowledge discovery or interactive multi-objective optimization that involves trial and failure. It is often necessary to modify data preprocessing and model parameters until the result achieves the desired properties. Besides the term clustering, there is a number of terms with similar meanings, including automatic classification, numerical taxonomy, botryology (from Greek βότρυς "grape"), typological analysis, and community detection. The subtle differences are often in the use of the results: while in data mining, the resulting groups are the matter of interest, in automatic classification the resulting discriminative power is of interest. Cluster analysis was originated in anthropology by Driver and Kroeber in 1932 and introduced to psychology by Joseph Zubin in 1938 and Robert Tryon in 1939 and famously used by Cattell beginning in 1943 for trait theory classification in personality psychology. (Wikipedia).
Cluster Analysis Steps In Business Analytics with R | Edureka
( R Training : https://www.edureka.co/r-for-analytics ) 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)
From playlist R Tutorial Videos
Clustering (2): Hierarchical Agglomerative Clustering
Hierarchical agglomerative clustering, or linkage clustering. Procedure, complexity analysis, and cluster dissimilarity measures including single linkage, complete linkage, and others.
From playlist cs273a
Introduction to Clustering Techniques | Mahout Clustering techniques | Mahout Clustering Tutorial
Watch Sample Class Recording: http://www.edureka.co/mahout?utm_source=youtube&utm_medium=referral&utm_campaign=clustering-tech 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
From playlist Machine Learning with Mahout
Data Science - Part VII - Cluster Analysis
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of clustering techniques, including K-Means, Hierarchical Clustering, and Gauss
From playlist Data Science
From playlist Clustering Algorithms
We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of simila
From playlist Data Science in Minutes
From playlist Thinking about Data
Mahout Clustering | Mahout Clustering Tutorial | Apache Mahout Clustering | Edureka
Watch Sample Class Recording: http://www.edureka.co/mahout?utm_source=youtube&utm_medium=referral&utm_campaign=clustering-tech-new 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
From playlist Machine Learning with Mahout
Two-step clustering using SPSS | A quick and effective guide
I demonstrate how to run two-step clustering using SPSS. For further information, please watch the following: Normality check: https://www.youtube.com/watch?v=UMq2YNoALZ8&list=PLTjlULGD9bNIY0Ipe54Qv0tSwuRiZOmZX Independent samples t-test: https://www.youtube.com/watch?v=clbr02KBGoY&list=
From playlist Clustering
MAE900_Session 13_Scientometrics_09/11/2021
To support the channel, I would like to invite you to join this channel to get access to perks: https://www.youtube.com/channel/UCfu2GCdjq50W-kL-cv3rcLw/join
From playlist Scientometrics & Bibliometrics
Latent class cluster analysis with free software Jamovi
In this video, I will show how to do a latent class cluster analysis with free software Jamovi. Please download Jamovi from this link: https://www.jamovi.org/download.html Recommended papers: 1. Latent class cluster analysis paper: https://journals.sagepub.com/doi/abs/10.1177/0276236619
From playlist Jamovi software
Predictive Modelling Techniques | Data Science With R Tutorial
🔥 Advanced Certificate Program In Data Science: https://www.simplilearn.com/pgp-data-science-certification-bootcamp-program?utm_campaign=PredictiveModeling-0gf5iLTbiQM&utm_medium=Descriptionff&utm_source=youtube 🔥 Data Science Bootcamp (US Only): https://www.simplilearn.com/data-science-bo
From playlist R Programming For Beginners [2022 Updated]
Lecturer: Dr. Erin M. Buchanan Summer 2020 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class - this video set covers the updated version with both R and Python. This video covers cluster analysis focusing on how to group together features of
From playlist Human Language (ANLY 540)
Scientometrics analysis 2: An introduction
In this video, I provide an introduction to Scientometrics analysis. The concepts briefly discussed include document co-citation analysis, author co-citation analysis, journal co-citation analysis, temporal metrics, structural metrics, the average silhouette score, Modularity Q, Betweennes
From playlist Scientometrics & Bibliometrics
Data Challenge Cornwall - Cluster Analysis to Create Personas without Bias
Link to slides: tinyurl.com/SmartlineClusterDataChallenge Slides include links to data and sample code. --- The Smartline Project ( https://www.smartline.org.uk ) brings together researchers, organisations, and businesses to understand the different challenges people face linked to healt
From playlist Data Challenge Cornwall 2021
R - Behavioral Profiles and Clustering
Lecturer: Dr. Erin M. Buchanan Summer 2019 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class. This video focuses on behavioral profiles and cluster analysis to help understand categories and their features. Note: these videos are part of liv
From playlist Human Language (ANLY 540)
Scientometrics analysis through CiteSpace 5: Timeline & cluster view
In this video, I demonstrate hot to use CiteSpace to perform a document co-citation analysis, which is a Scientometrics analysis technique. The concepts briefly discussed include document co-citation analysis, author co-citation analysis, journal co-citation analysis, temporal metrics, str
From playlist Scientometrics & Bibliometrics
What is cluster sampling? Comparison to stratified sampling. Advantages and disadvantages. Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creator-spring.com/listing/sampling-in
From playlist Sampling