B.TECH - Semester 7 data mining and information retrieval Question Paper 2013 (dec)
Practice authentic previous year university questions for better exam preparation.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (a) Compute the Euclidean distance between the two objects.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (b) Compute the Manhattan distance between the two objects.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (c) Compute the Minkowski distance between the two objects, using $q=3$.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (d) Why are the above 3 functions called as distance functions.
- With examples compare feature extraction and feature construction.
- Describe about SVM classifier.
- Given a query "what is data mining", how does a search engine retrieve the related documents. （Answer one full question from each module．Each question carries 20 marks） 6．（a）Elaborate on how discretization and binarization are performed． （b）Explain the basic data mining tasks with examples．Check o...
- (a) Given the following data, identify the type of the attributes and draw a decision tree to classify a creature as fish, bird, human, cat or horse. | Index | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | Height <br> (m) | 0.1 | 0.2 | 1....
- (b) Discuss the advantages and disadvantages of using the decision tree classifier with examples. Can a rule based classifier be derived from a decision tree classifier? If so, how?
- (a) Describe the density based clustering algorithms used to discover clusters of arbitrary shape.
- (b) Describe the grid based clustering algorithms with information on how statistical information and wavelet transforms are useful for clustering.
- (a) Compare the various constraint based clustering methods.
- (b) What is model based clustering? Explain the model based clustering techniques.
- (a) Compare spatial and temporal mining.
- (b) Elaborate on how similarity search, classification and prediction analysis of multimedia data performed.
- (a) A database has five transactions. Let min_sup $=60 \%$ and $\min \_$conf $=80 \%$. TID Items bought | T100 | $12,13,14,16,17$ | | :--- | :--- | | T200 | $11,13,15,16,17$ | | T300 | $11,14,19,110$ | | T400 | $11,15,16,19,110$ | | T500 | $13,15,16,110,111$ |
- Consider the following variable transformations. State the effect of the transformations. (a) $1 / x$
- Consider the following variable transformations. State the effect of the transformations. (b) $|x|$
- Consider the following variable transformations. State the effect of the transformations. (c) standardizing using mean and standard deviation
- Consider the following variable transformations. State the effect of the transformations. (d) standardizing using median and absolute standard deviation
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