Question: What is the major difference between cluster analysis and classification?
What is the major difference between cluster analysis and classification?
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The major difference between cluster analysis and classification lies in their objectives and methods Objective Cluster Analysis Cluster analysis is an unsupervised learning technique that aims to group similar data points together based on their inherent similarities or dissimilarities It does not have predefined categories or labels for the groups instead it discovers patterns or clusters within the data Classification Classification is a supervised learning technique where the goal is to assign predefined categories or labels to data points based on their features The algorithm is trained on a labeled dataset and learns to make predictions on new unseen data Input Data Cluster Analysis It works with unlabeled data and focuses on finding natural groupings or clusters within the data without any prior knowledge of what those clusters might represent Classification It requires a labeled dataset where each data point is assigned to a specific class or category The algorithm learns to classify new data points into these predefined classes Output Cluster Analysis The output of cluster analysis is a ... View full answer
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