Fall 2024: Data Mining Lab

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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 September 2024 )

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

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. Amar Kumar (25065)
  4. Kunal Verma (25073)
  • Dataset:
  • Report:
  • Project Presentation:
2 NIRF Ranking Prediction
  1. Abhishek Prasad (25007)
  2. Vishal Kumar (25014)
  3. Nitish Kumar (25023)
  4. 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. Ansh Raj (250xx)
  2. Uday Raj Verma (250xx)
  3. Astitwa Rawar (250xx)
  4. Ritesh Dhawan (250xx)
  • Dataset:
  • Report:
  • Project Presentation:
9 CreditMap: Exploring Credit Score Patterns through Data Mining
  1. Himanshu Singh (250xx)
  2. Garvit Kumar (250xx)
  3. Abhishek (250xx)
  4. Mayank (250xx)
  • Dataset:
  • Report:
  • Project Presentation:
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