How Cluster Analysis Can Transform Your Marketing Strategy
What do all great marketing strategies have in common? They truly understand the customer—who they are, how they think, what they need, and how they behave. Getting this level of insight is only possible by effectively grouping customers into distinct groups based on their age, location, shopping habits, social media usage, and so much more. […]
What is a Dendrogram?
What is a cluster analysis dendrogram? A dendrogram (or clustering dendrogram) is a diagram that shows the hierarchical relationship between objects. It is most commonly created as an output from hierarchical clustering. Dendrograms are used in machine learning and data science to help visualize clustering. The main use of a dendrogram is to work out the […]
How to Work Out the Number of Clusters in Cluster Analysis
Cluster analysis techniques (most of them) require users to specify the number of clusters that they require. There are six broad classes of approaches to choosing the number of clusters: penalized fit heuristics, statistical tests, the extent of association with other data, replicability, no small classes, and domain-usefulness. Penalized fit heuristics Provided there are no […]
K-Means Clustering | The Easier Way To Segment Your Data
The k-means clustering algorithm is a cornerstone of modern data analysis, widely used for segmenting data into meaningful groups. In this article, we’ll provide a clear k-means clustering definition, explain how the algorithm k-means works step-by-step, and show you how to use it for market segmentation and other practical applications. k-means clustering definition The k-means clustering algorithm is an unsupervised […]
What is Cluster Analysis?
TL;DR: What is Cluster Analysis? Cluster analysis groups similar objects into clusters based on shared characteristics. It’s especially useful for uncovering patterns in high-dimensional data that can’t be easily visualized. Cluster analysis refers to algorithms that group similar objects into groups called clusters. The endpoint of cluster analysis is a set of clusters, where each […]
How To Do K-Means Cluster Analysis In Displayr
The k-Means cluster analysis algorithm is a method for grouping similar cases into groups, or clusters. The final clusters will be different from each other, while the cases within a cluster are broadly similar to each other. In Displayr, we can run a k-Means Cluster Analysis by creating a k-Means object, selecting the clustering variables […]
Clustering with Missing Values: Why Latent Class Analysis Is The Way
When it comes to segmenting your data, it’s not uncommon to deal with missing values. It might be because certain questions have not been asked in a survey or because of ‘don’t know’ responses that have come through in your data. Most of the widely used cluster analysis algorithms can be highly misleading or can […]
