From the course: Advanced Python in Excel: Machine Learning
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Clustering techniques for market segmentation
From the course: Advanced Python in Excel: Machine Learning
Clustering techniques for market segmentation
- [Instructor] Now we have clustering. Clustering is an unsupervised machine learning technique used to group similar data points together based on their features. It's particularly useful for market segmentation business because it can identify distinct customer groups. The clustering algorithm works by finding natural groupings in the data. Common algorithms include k-means, hierarchical clustering or DBSCAN, each one with its own method of defining and identifying clusters. In K-means clustering, for example, the algorithm partitions the data into k clusters where each data point belongs to a cluster with the nearest mean. The goal is to minimize the variance with each cluster. The formula for k-means involves iteratively updating the cluster centroids and reassigning data points to the nearest centroid until convergence, ensuring that the clusters are well defined and stable. In business, you can use it for segmenting customers based on purchasing behavior, identifying similar…
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