Resources for MMA, MMAI, and GMMA 869
Name | Source | Instances | Features | Target |
---|---|---|---|---|
diabetes | Kaggle | 769 | ID: 1 Numeric: 8 |
diabetes 0 : 65%1 : 35% |
German Credit | UCI | 1000 | Numeric: 61 | Class Good : 70%Bad :35% |
HR | UCI | 14999 | Numeric: 7 Categorical: 2 |
left 0 : 76%1 : 24% |
Adult (1994 USA Census) | UCI | 32561 | Numeric: 6 Categorical: 8 |
high_salary 0 :76%1 : 24% |
Portugese Bank Marketing | UCI | 4521 | Numeric: 7 Categorical: 9 |
y no : 88%yes : 12% |
European Credit Card | Przemyslaw Zientala | 142403 | Time: 1 Numeric: 29 |
Class 0 : 99.8%1 : 0.2% |
Marketing (Synthetic) | generate_data.ipynb | 500 | Numeric: 2 | Bought 0 : 50%1 : 50% |
German Credit (Synthetic) | UCI | 1000 | Numeric: 48 Categorical: 8 |
BadCredit 0 : 70%1 : 30% |
ISLR Student Credit Default | ISLR | 10000 | ID: 1 Numeric: 2 Categorical: 1 |
default No : 97%Yes : 3% |
Mall Customers | Kaggle | 200 | ID: 1 Numeric: 3 Categorical: 1 |
N/A |
Groceries | Machine Learning with R | 9835 | Binary: 169 | N/A |
Orange Juice Purchase | ISLR | 1070 | ID: 1 Numeric: 17 |
Purchase CH : 61%MM : 39% |
Groceries | Unknown | 505 | Numeric: 4 | N/A |