What are the advantages of dbscan clustering algorithm

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Assignment

Question One

a. Q1.Data objects may belong to more than one class at a time. In such cases it is difficult to assess classification accuracy. Mention your comment on what criteria you would use to compare different classifiers modeled using the same data.

Question Two

a. Classify the following classification techniques to either eager or lazy classification.
b. Decision tree, case-based reasoning, Bayesian, neuralnetwork, k-mean, k-nearest neighbor.
c. Compare and contrast Eager and Lazy classification methods.

Question Three

a) Explain dendrogram. What could be the possible reason(s) for producing two different dendrograms using agglomerative clustering algorithm for the same dataset?

b) In which cases K-Means clustering algorithm fails to give good results?

Question Four

a) What are the advantages of DBSCAN clustering algorithm?

b) Assume, you want to cluster observations into 3 clusters using K-Means clustering algorithm. After first iteration three clusters (C1, C2,

C3) havethe following observations:
C1: {(4,4), (5,5), (6,6)}
C2: {(0,6), (4,6)}
C3: {(3,9), (11,11)}

Find the cluster centroid of each cluster?

Reference no: EM131739055

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