he cophenetic coefficient is a measure used to evaluate the quality of a hierarchical clustering solution. It quantifies how faithfully the hierarchical structure (dendrogram) preserves the original pairwise distances or dissimilarities between data points. Here’s how it works: A high cophenetic coefficient suggests that the hierarchical clustering solution accurately captures the underlying structure of the…
he silhouette coefficient is a measure of how well-separated clusters are in a clustering analysis. It provides a way to assess the quality of clustering by evaluating both the cohesion within clusters and the separation between clusters. The silhouette coefficient ranges from -1 to 1, with higher values indicating better-defined clusters. Here’s how the silhouette…
Model coefficients, also known as regression coefficients or weights, are the values assigned to the features (independent variables) in a regression model. In a linear regression model, the relationship between the input features (X) and the predicted output (y) is represented as: Here: The model coefficients are estimated during the training of the regression model.…
