-
Notifications
You must be signed in to change notification settings - Fork 0
/
readme.txt
55 lines (37 loc) · 3.33 KB
/
readme.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
# data_mining_projects
PREREQUISITES(INSTALLED IN COMPUTER AND IN YOUR BRAIN) FOR PROJECTS :
PYTHON (HOW TO INSATLL AND USE ? SEE YT OR GOOGLE)
Jupyter Notebook (HOW TO INSATLL AND USE ? SEE YT OR GOOGLE)
ANACONDA (HOW TO INSATLL AND USE ? SEE YT OR GOOGLE)
ALGO KNOWLEDGE (HOW TO KNOW ? SEE YT OR GOOGLE)
OR
GO WITH WHICH EVER YOU KNOW!
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
PROBLEM STATEMENT PROJECT A : Fraud Detection: Use decision trees to detect fraud in financial transactions. Use a dataset of financial transactions and their corresponding labels (fraudulent or non fraudulent) to train the decision tree. Then use the trained model to predict whether new transactions are fraudulent or not.
PROJECT A DATAFILE LINK :
https://www.kaggle.com/datasets/ealtman2019/credit-card-transactions
PROJECT A REFERENCES LINK :
https://trenton3983.github.io/files/projects/2019-07-19_fraud_detection_python/2019-07-19_fraud_detection_python.html
https://pages.databricks.com/rs/094-YMS-629/images/financial-fraud-detection-decision-tree.html
https://github.com/yashaswibiyahut/Credit-Card-Fraud-Detection/blob/master/Credit%20Card%20Fraud%20Detection.ipynb
https://github.com/limkhashing/Credit-Card-Fraud-Detection/blob/master/Python/Fraud%20detection%20with%20DT%20CART%20Cardzone.ipynb
https://github.com/aameerhamza1801/Credit-Card-Fraud-Detection-Using-Different-ML-Techniques/blob/master/FraudDetection.ipynb
https://www.kaggle.com/code/jamiemorales/decision-tree-classifier-fraud-detection
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
PROBLEM STATEMENT PROJECT B : Crime Analysis: Use DBSCAN clustering algorithm to analyze crime patterns in a city. Use a dataset of crime data and their corresponding features to train the algorithm.Then use the trained model to group similar crime patterns and identify hotspots.
PROJECT B DATAFILE LINK :
SOORY I LOST THE LINK FOR THIS :.(
PROJECT B REFERENCES LINK : :
https://github.com/mcoric96/Crime-analysis
https://github.com/Abhik35/Assignment-DBSCAN-Clustering-Crimes-/blob/main/Assignment-DBSCAN%20Clustering%20(Crimes).ipynb
https://github.com/anujahlawat/crime_data-DBSCAN
https://github.com/anujahlawat/crime_data-DBSCAN
https://github.com/vaitybharati/Assignment-07-DBSCAN-Clustering-Crimes-
https://github.com/Manu-Gr/DB-SCAN---Assignment---Crime-Dataset
https://github.com/topics/dbscan-clustering?q=dbscan+crime
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
OTHER IMP STUFFS TO BUILD PROJECT :
THIS LINKS EXPLAIN HOW TO MODIFY YOUR CODE TO GIVE CUSTOM INPUT AND TESTCASES
https://thecleverprogrammer.com/2021/11/29/how-to-give-inputs-to-a-machine-learning-model #:~:text=To%20give%20inputs%20to%20a%20machine%20learning%20model%2C%20you%20have,output%20based%20on%20the%20inputs.
https://stackoverflow.com/questions/58712891/testing-prediction-model-with-user-input
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------