Clustering: Difference between revisions
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'''Clustering''' is an [[unsupervised learning]] technique. It is used for grouping data points, or objects that are somehow similar. | '''Clustering''' is an [[unsupervised learning]] technique. It is used for grouping data points, or objects that are somehow similar. Clustering means finding clusters in a dataset, unsupervised.<ref>[https://www.coursera.org/learn/machine-learning-with-python/lecture/Nlxjw/intro-to-clustering Intro to Clustering]Coursera</ref> | ||
== Types pof clustering == | == Types pof clustering == | ||
Revision as of 20:02, 31 March 2020
Clustering is an unsupervised learning technique. It is used for grouping data points, or objects that are somehow similar. Clustering means finding clusters in a dataset, unsupervised.[1]
Types pof clustering
Some divide clustering into two subgroups[2]:
- Hard clustering: Each data point either belongs to a cluster completely or not.
- Soft clustering: A probability or likelihood is assigned for putting data points into separate clusters.
Algorithms
Some of the commonly used clustering algorithms are[3]:
References
References
- ↑ Intro to ClusteringCoursera
- ↑ An Introduction to Clustering and different methods of clusteringanalyticsvidhya.com
- ↑ Real World Applications of Unsupervised Learningpythonistaplanet.com