Business Intelligence Assignment | Business & Finance homework help
There is a major difference in classification and clustering. It all comes down to the nature or output. The main difference between classification and clustering is the nature of the output. Classification involves training a model using prelabeled data to make future predictions. While clustering relies more on unlabeled information, it looks for similarities or patterns among objects/data points.
Additionally, classification tasks focus more on individual entities; for example categorizing items into predefined classes such as “spam” or “not spam”, whereas clustering uses larger sets of data to group similar observations together without necessarily ascribing labels to each resulting cluster. In summary, both techniques can be powerful tools when it comes to analytical problem solving but their application depends heavily upon the specific task at hand – whether one requires discrete categories or high-level trends across large amounts of input data.