Q1. Explain the difference between clustering and classification Q2.Describe the

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Q1. Explain the difference between clustering and classification

Q2.Describe the k-means algorithm.

Q3.Suppose that you are employed as a data-mining consultant for an Internet search engine company. Describe how data mining can help the company by giving specific examples of how techniques, such as clustering, classification, association rule mining, and anomaly detection can be applied.

Q4.Explain the reason behind describing artificial neural networks (ANN) as "black box”. Then propose one technique to overcome this criticism.

Q5.Discuss one advantage and one disadvantage of Support Vector Machines (SVM) compared to artificial neural networks (ANN).

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Q1)

Clustering

Classification

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Clustering

Classification

In clustering there is no prior knowledge of the classes In classification there is prior knowledge of classes To suggest groups in the data by discovering the new patterns in the data Classify the data into classes through prior knowledge of data Used to explore the data to find new insights in the data It is used so that it is known where to place future observations Unlabelled data samples are used in clustering Labelled data samples are used in classification k-means clustering is an example of clustering Bayesian classifiers is an example of classification

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