Difference between revisions of "Fall 2024: Data Mining Lab"

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== '''Lab 3:''' ( week of 16<sup>th</sup> &  23<sup>rd</sup>  September 2024 ) ==
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== '''Lab 3:''' ( week of 16<sup>th</sup>, 23<sup>rd</sup> & 30<sup>th</sup>September 2024 ) ==
 
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| style="width: 60%" | Writing/Review of Chapter 1 and Chapter 3 of Project
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| style="width: 60%" | Writing/Review of Chapter 1, Chapter 3, and Chapter 4 of Project Report
 
| style="width: 15%" |  Project Work
 
| style="width: 15%" |  Project Work
 
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== '''Lab 4:''' ( week of 7<sup>th</sup> October 2024 ) ==
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! Q. NO. 
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! Program 
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! Practical No. 
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! Remarks
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| style="width: 8%"  | 1
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| style="width: 60%" | Apply simple K-means algorithm for clustering any dataset. Compare the performance of clusters by varying the algorithm parameters. For a given set of parameters, plot a line graph depicting MSE obtained after each iteration.
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| style="width: 15%" |  Practical No. 3
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| '''Dataset:''' [http://mkbhandari.com/mkwiki/data/fall2024/dm/datasets/Mall_Customers.csv '''Mall_Customers.csv'''] <br>
 +
'''Download from data from kaggle:''' [https://www.kaggle.com/datasets/vjchoudhary7/customer-segmentation-tutorial-in-python Mall Customer Segmentation Data]
 
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| style="width: 45%" | Understanding the Monsoon Pattern in Eastern Gangatic Plain  
 
| style="width: 45%" | Understanding the Monsoon Pattern in Eastern Gangatic Plain  
 
| style="width: 25%" |   
 
| style="width: 25%" |   
−
# Akshary Sharma (25019)
+
# '''Akshary Sharma (25019)'''
 
# Abhay Yadav (25040)
 
# Abhay Yadav (25040)
 +
# Anuj Gupta (25042)
 
# Amar Kumar (25065)
 
# Amar Kumar (25065)
 
# Kunal Verma (25073)
 
# Kunal Verma (25073)
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|-
 
|-
 
|2|| NIRF Ranking Prediction||  
 
|2|| NIRF Ranking Prediction||  
−
# Abhishek Prasad (25007)
+
# '''Abhishek Prasad (25007)'''
 
# Vishal Kumar (25014)
 
# Vishal Kumar (25014)
 
# Nitish Kumar (25023)
 
# Nitish Kumar (25023)
 +
# Anshu Kumar Dubey (25036)
 
# Sunny Chauhan (25050)
 
# Sunny Chauhan (25050)
 
|  
 
|  
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* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|3|| Student Performance Prediction||  
+
|3|| Student Performance Prediction ||  
−
# Himanshu Kumar (25016)
+
# '''Himanshu Kumar (25016)'''
 
# Kanan Pal (25072)
 
# Kanan Pal (25072)
 
# Khushboo Yadav (25082)
 
# Khushboo Yadav (25082)
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|4|| FIFA Prediction ||  
 
|4|| FIFA Prediction ||  
 
# Arihant (25003)
 
# Arihant (25003)
−
# Ayush Pundir (25027)
+
# '''Ayush Pundir (25027)'''
 
# Pratyush (25060)
 
# Pratyush (25060)
 
# Ashish (25066)
 
# Ashish (25066)
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|5|| Breast Cancer Prediction ||  
 
|5|| Breast Cancer Prediction ||  
 
# Vidhan (25044)
 
# Vidhan (25044)
−
# Sandeep Kumar Sharma (25047)
+
# '''Sandeep Kumar Sharma (25047)'''
 
# Ayushman Pandey (25094)
 
# Ayushman Pandey (25094)
 
# Tanishk Panchal (25095)
 
# Tanishk Panchal (25095)
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# Shatrughan  (25084)
 
# Shatrughan  (25084)
 
# Om Ranjan (25085)
 
# Om Ranjan (25085)
−
# Aman Sagar (25086)
+
# '''Aman Sagar (25086)'''
 
|  
 
|  
 
* Dataset:  
 
* Dataset:  
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|7|| Olympic Data Analysis and Prediction ||  
 
|7|| Olympic Data Analysis and Prediction ||  
 
# Kusum (25002)
 
# Kusum (25002)
−
# Aditya Kumar (25012)
+
# '''Aditya Kumar (25012)'''
 
# Divyanshi (25021)
 
# Divyanshi (25021)
 
# Tushar Rana (25064)
 
# Tushar Rana (25064)
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|-
 
|-
 
|8|| Credit Card Fraud Detection ||  
 
|8|| Credit Card Fraud Detection ||  
−
# Ansh Raj (250xx)
+
# Ritesh Dhawan (25037)
−
# Uday Raj Verma (250xx)
+
# Bitthal Varshney (25041)
−
# Astitwa Rawar (250xx)
+
# Ansh Raj (25081)
−
# Ritesh Dhawan (250xx)
+
# '''Uday Raj Verma (25083)'''
 +
# Astitwa Rawat (25088)
 
|  
 
|  
 
* Dataset:  
 
* Dataset:  
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|-
 
|-
 
|9|| CreditMap: Exploring Credit Score Patterns through Data Mining ||  
 
|9|| CreditMap: Exploring Credit Score Patterns through Data Mining ||  
−
# Himanshu Singh (250xx)
+
# Himanshu Singh (25017)
−
# Garvit Kumar (250xx)
+
# '''Garvit Kumar (25018)'''
−
# Abhishek (250xx)
+
# Mayank  (25022)
−
# Mayank (250xx)
+
# Abhishek Kumar Singh(25032)
 +
|
 +
* Dataset:
 +
* Report:
 +
* Project Presentation:
 +
|-
 +
|10|| Movie Recommendation System ||
 +
# Tanya Agrahari (25030)
 +
# Prakash Mishra (25035)
 +
# '''Adarsh Singh (25074)'''
 +
# Shivam Verma (25078)
 +
|
 +
* Dataset:
 +
* Report:
 +
* Project Presentation:
 +
|-
 +
|11|| Wine Quality Prediction ||
 +
# '''Shivam Soni (250xx)'''
 +
# ⁠Kashif (250xx)
 +
# Akash Pathak (250xx)
 +
# ⁠Priyanshu Sachan (250xx)
 
|  
 
|  
 
* Dataset:  
 
* Dataset:  

Latest revision as of 21:54, 26 November 2024

Instructions

  • Please be on time to avoid the Attendance Penalty.
  • Please sign on the Attendance Register before your take a seat.
  • Please put your mobile phone in the Silent Mode.
  • Each lab assignment needs to be submitted in the Google Classroom for evaluation(will be notified in the GC lab-wise, submit before the deadline).
  • Turn off(shut down) your assigned computer and arrange the chair before you leave the lab.

Guidelines

Lab 0: Getting Started ( week of 05th & 12th August 2024 )

Q. NO. Program Practical No. Remarks
1 https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial1/tutorial1.html Practice Set No. 1 Introduction to Python
2 https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial2/tutorial2.html Practice Set No. 2 Introduction to Numpy and Pandas
3 https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial3/tutorial3.html Practice Set No. 3 Data Exploration

Lab 1: ( week of 19th & 26th August 2024 )

Q. NO. Program Practical No. Remarks
1 Apply data cleaning techniques on any dataset (e.g. Chronic Kidney Disease dataset from UCI repository). Techniques may include handling missing values, outliers and inconsistent values. Also, a set of validation rules may be specified for the particular dataset and validation checks performed. Practical No. 1 Dataset: kidneyDisease.csv

Download from Kaggle: Chronic KIdney Disease dataset
Tutorial: Tutorial on Handling Missing values

Lab 2: ( week of 2nd & 9th September 2024 )

Q. NO. Program Practical No. Remarks
1 Apply data pre-processing techniques such as standardization/normalization, transformation, aggregation, discretization/binarization, sampling etc. on any dataset Practical No. 2 Dataset: rain.csv

Download from data.gov.in: Rainfall in India

Lab 3: ( week of 16th, 23rd & 30thSeptember 2024 )

Q. NO. Program Practical No. Remarks
1 Writing/Review of Chapter 1, Chapter 3, and Chapter 4 of Project Report Project Work

Lab 4: ( week of 7th October 2024 )

Q. NO. Program Practical No. Remarks
1 Apply simple K-means algorithm for clustering any dataset. Compare the performance of clusters by varying the algorithm parameters. For a given set of parameters, plot a line graph depicting MSE obtained after each iteration. Practical No. 3 Dataset: Mall_Customers.csv

Download from data from kaggle: Mall Customer Segmentation Data

Projects

Team No. Project Title Team Members Outcomes/Remarks
1 Understanding the Monsoon Pattern in Eastern Gangatic Plain
  1. Akshary Sharma (25019)
  2. Abhay Yadav (25040)
  3. Anuj Gupta (25042)
  4. Amar Kumar (25065)
  5. Kunal Verma (25073)
  • Dataset:
  • Report:
  • Project Presentation:
2 NIRF Ranking Prediction
  1. Abhishek Prasad (25007)
  2. Vishal Kumar (25014)
  3. Nitish Kumar (25023)
  4. Anshu Kumar Dubey (25036)
  5. Sunny Chauhan (25050)
  • Dataset:
  • Report:
  • Project Presentation:
3 Student Performance Prediction
  1. Himanshu Kumar (25016)
  2. Kanan Pal (25072)
  3. Khushboo Yadav (25082)
  4. Diksha Joshi (25091)
  • Dataset:
  • Report:
  • Project Presentation:
4 FIFA Prediction
  1. Arihant (25003)
  2. Ayush Pundir (25027)
  3. Pratyush (25060)
  4. Ashish (25066)
  • Dataset:
  • Report:
  • Project Presentation:
5 Breast Cancer Prediction
  1. Vidhan (25044)
  2. Sandeep Kumar Sharma (25047)
  3. Ayushman Pandey (25094)
  4. Tanishk Panchal (25095)
  • Dataset:
  • Report:
  • Project Presentation:
6 YouTube spam comments classification
  1. Devesh Chauhan (25011)
  2. Shatrughan (25084)
  3. Om Ranjan (25085)
  4. Aman Sagar (25086)
  • Dataset:
  • Report:
  • Project Presentation:
7 Olympic Data Analysis and Prediction
  1. Kusum (25002)
  2. Aditya Kumar (25012)
  3. Divyanshi (25021)
  4. Tushar Rana (25064)
  • Dataset:
  • Report:
  • Project Presentation:
8 Credit Card Fraud Detection
  1. Ritesh Dhawan (25037)
  2. Bitthal Varshney (25041)
  3. Ansh Raj (25081)
  4. Uday Raj Verma (25083)
  5. Astitwa Rawat (25088)
  • Dataset:
  • Report:
  • Project Presentation:
9 CreditMap: Exploring Credit Score Patterns through Data Mining
  1. Himanshu Singh (25017)
  2. Garvit Kumar (25018)
  3. Mayank (25022)
  4. Abhishek Kumar Singh(25032)
  • Dataset:
  • Report:
  • Project Presentation:
10 Movie Recommendation System
  1. Tanya Agrahari (25030)
  2. Prakash Mishra (25035)
  3. Adarsh Singh (25074)
  4. Shivam Verma (25078)
  • Dataset:
  • Report:
  • Project Presentation:
11 Wine Quality Prediction
  1. Shivam Soni (250xx)
  2. ⁠Kashif (250xx)
  3. Akash Pathak (250xx)
  4. ⁠Priyanshu Sachan (250xx)
  • Dataset:
  • Report:
  • Project Presentation:
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