05-05-2012, 12:56 PM
DMW
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1) Figure shows a multilayer feed-forward neural network. Let the learning rate be 0.9. The initial weight and bias value of the network are given in the table along with the first training tuple, whose class label is 1. Find out the updated weights and Bias value.
X1 X2 X3 W14 W15 W24 W25 W34 W35 W46 W56 θ4 θ5 θ6
1 0 1 0.2 -0.3 0.4 0.1 -0.5 0.2 -0.3 -0.2 -0.4 0.2 0.1
2) Explain Multilayer Feed Forward Neural Network with diagram
3) Compute Information Gain for Age, Income, Student and Credit_Rating attributes.
RID Age Income Student Credit_Rating Class: buys-computer
1 Youth High No Fair No
2 Youth High No Excellent No
3 Middle-aged High No Fair Yes
4 Senior Medium No Fair Yes
5 Senior Low Yes Fair Yes
6 Senior Low Yes Excellent No
7 Middle-aged Low Yes Excellent Yes
8 Youth Medium No Fair No
9 Youth Low Yes Fair Yes
10 Senior Medium Yes Fair Yes
11 Youth Medium Yes Excellent Yes
12 Middle-aged Medium No Excellent Yes
13 Middle-aged High Yes Fair Yes
14 Senior Medium No Excellent No
4) What is Prediction? Explain Linear Regression and Non Linear Regression.
5) Given two objects represented by the tuples (22, 1, 42, 10) and (20, 0, 36, 8).
i. Compute the Euclidean distance between the two objects.
ii. Compute the Manhattan distance between the two objects.
6) Why Naïve Bayesian classification is called “Naïve”? Briefly outline the major ides of Naïve Bayesian classification.
7) What is hierarchical clustering? Explain chameleon hierarchical clustering in detail.
8) In the given table1 the data tuples are described by the attributes age, income student and credit-rating. The class label attribute, buys-computer, has two distinct values (namely {yes, no}. C1 corresponds to the class buys-computer=yes and C2 corresponds to buys-computer=no. Classify the tuple X=(age=youth, income=medium, student=yes, credit-rating=fair) using naive Bayesian classification.
Note: (Refer table no 1 of question no 1)
9) What is Clustering? Explain Major Clustering Methods.
10) Explain OLAP tools and Servers.
11) The following table shows the mid term and final exam grades obtained for students in a database course.
X (Experience) 3 8 9 13 3 6 11 21 1 16
Y (Salary) 30 57 64 72 36 43 59 90 20 83
i. Plot the data. Do x and y seem to have a Linear relationship?
ii. Use the method of Least Squares to find an equation for the Prediction of salary on the basis of experience.
iii. Predict the salary of a person how is experience is 10 years.
12) What is Aggregation? Explain steps to design a summary table
13) Explain the effects of security on different parts of datawarehouse
14) Write short note on:
i. Disaster Recovery.
ii. Tunning Datawarehouse.
iii. Back up.