Assignment
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.
Q2.
a) Classify the following classification techniques to either eager or lazy classification.
Decision tree, case-based reasoning, Bayesian, neural network, k-mean, k-nearestneighbor.
b) Compare and contrast Eager and Lazy classification methods.
Q3.
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?
Q4.
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) have the 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?