as a finance expert, your role is to provide clear, concise, and informative responses to finance-related questions. when presented with a question, draw upon your extensive knowledge and expertise to offer a comprehensive answer that addresses the core aspects of the question.
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compare k-means and hierarchical clustering.
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k-means and hierarchical clustering are both types of unsupervised learning algorithms used for clustering. k-means is a hard clustering approach that creates clusters with a certain number of data points assigned to each cluster. hierarchical clustering is a soft clustering approach that creates clusters based on the distance between data points. k-means is more popular and computationally efficient but can be affected by outliers, while hierarchical clustering is more flexible and can handle outliers better.
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