# CS - UR Introduction to Kaggle Competitions — Data

来源：https://www.kaggle.com/competitions/cs-ur-introduction-to-kaggle-competitions/data

采集时间：2026-10-24T19:22:14Z

## Files
*   **train.csv** - the training set
*   **test.csv** - the test set
*   **sample_submission.csv** - a sample submission file in the correct format

## Attribute Information

Input features in order:
- 1 **CRIM:** per capita crime rate by town
- 2  **ZN:** proportion of residential land zoned for lots over 25,000 sq.ft.
- 3  **INDUS:** proportion of non-retail business acres per town
- 4 **CHAS:** Charles River dummy variable (1 if tract bounds river; 0 otherwise)
- 5 **NOX:**nitric oxides concentration (parts per 10 million) [parts/10M]
- 6 **RM:** average number of rooms per dwelling
- 7 **AGE:** proportion of owner-occupied units built prior to 1940
- 8 **DIS:** weighted distances to five Boston employment centres
- 9 **RAD:** index of accessibility to radial highways
- 10 **TAX:** full-value property-tax rate per $10,000 [$/10k]
- 11 **PTRATIO:** pupil-teacher ratio by town
- 12 **B:** The result of the equation B=1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
- 13 **LSTAT:** % lower status of the population

Output variable:
-1 **MEDV:** Median value of owner-occupied homes in $1000's [k$]

Source
StatLib - Carnegie Mellon University


Your task is to estimate the price of a house using the variables mentioned above.