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CS725 Assignment 4 Solution and Discussion
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Data Mining
Virtual university of Pakistan
Assignment # 01
Total Points: 40
Data Mining (CS725)
Please read the instructions before stepping in to the assignment solution. Please try to complete and upload your assignment on or before due date. No assignment will be considered after due date through email.
Instructions:
Please apply/ perform all the steps.
Copying from other students or any other source will be
marked as ZERO.
Screenshots of assignment solution will not be considered.
Assignment solution must be typed.
Screenshots of Mathematical Equation will lead to marks deduction.
No assignment will be entertained through email.
Be specific and to the point in assignment solution. No assignment after due date will be accepted.
Due Date: November 15th, 2019Data Mining Virtual university of Pakistan
Question# 01
Consider an undergraduate class having four core subjects as follows:
Computer programming
Data structures
Analysis of algorithms
Digital logic design.
(30pts)
As per university policy, a student has to score minimum marks as follows to clear the semester.
a) Min-max normalization by considering maximum as 1 and minimum as 0 b) Z-score and discuss every calculated z-score result.
Question# 02 (10pts)
a) Compute the cosine similarity for the below mentioned documents:
D1= Ali loves me more than Akram loves me
D2= Shahzain likes me more than Ali loves me.Data Mining Virtual university of Pakistan
b) Consider the university students records mentioned below and compute Euclidean distance:
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Fall 2019 Data Mining Virtual university of Pakistan
Data Mining (CS725)
Assignment # 01 Total Points: 50
Please read the instructions before stepping in to the assignment solution. Please try to complete and upload your assignment on or before due date. No assignment will be considered after due date through email.
Instructions:
Please apply/ perform all the steps.
Copying from other students or any other source will be
marked as ZERO.
Screenshots of assignment solution will not be considered.
Assignment solution must be typed.
Screenshots of Mathematical Equation will lead to marks deduction.
No assignment will be entertained through email.
Be specific and to the point in assignment solution. No assignment after due date will be accepted.
Due Date: January 16th, 2020
1Fall 2019 Data Mining
Actual Predicted Yes No Yes 70 30 No 40 60
Virtual university of Pakistan
Question# 01
Consider the following dataset mentioned below:
(10pts)Now calculate the following:
i. Sensitivity
ii. Specificity
iii. Error rate
Question# 02
(40pts)
Consider the following class-labeled training tuples from the weather forecast dataset mentioned below:
a) Calculate the Gain for every mentioned attribute and identify which attribute will be chosen for splitting?
b) Compute the Gini index for the overall collection of training dataset
CS725 Assignment 3 Solution and Discussion
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Fall 2019 Data Mining Virtual university of Pakistan
Data Mining (CS725)
Assignment # 01 Total Points: 50
Please read the instructions before stepping in to the assignment solution. Please try to complete and upload your assignment on or before due date. No assignment will be considered after due date through email.
Instructions:
Please apply/ perform all the steps.
Copying from other students or any other source will be
marked as ZERO.
Screenshots of assignment solution will not be considered.
Assignment solution must be typed.
Screenshots of Mathematical Equation will lead to marks deduction.
No assignment will be entertained through email.
Be specific and to the point in assignment solution. No assignment after due date will be accepted.
Due Date: January 16th, 2020
1Fall 2019 Data Mining
Virtual university of Pakistan
Question# 01
Consider the following dataset mentioned below:
(10pts)Actual Predicted Yes No Yes 70 30 No 40 60 Now calculate the following:
i. Sensitivity
ii. Specificity
iii. Error rate
Question# 02
(40pts)
Consider the following class-labeled training tuples from the weather forecast dataset mentioned below:
a) Calculate the Gain for every mentioned attribute and identify which attribute will be chosen for splitting?
b) Compute the Gini index for the overall collection of training dataset