K-means clustering is a partitioning method and as anticipated, this method decomposes a dataset into a set of disjoint clusters. Given a dataset, a partitioning method constructs several partitions of this data, with each partition representing a cluster. These methods relocate instances by moving them from one cluster to another, starting from an initial partitioning.
Partitioning-based clustering methods - K-means algorithm
by Giuseppe Ciaburro
MATLAB for Machine Learning
- Preface
- Getting Started with MATLAB Machine Learning
- Importing and Organizing Data in MATLAB
- From Data to Knowledge Discovery
- Finding Relationships between Variables - Regression Techniques
- Pattern Recognition through Classification Algorithms
- Identifying Groups of Data Using Clustering Methods
- Simulation of Human Thinking - Artificial Neural Networks
- Improving the Performance of the Machine Learning Model - Dimensionality Reduction
- Machine Learning in Practice
Partitioning-based clustering methods - K-means algorithm
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