Data
Boston-house-price-data

Boston-house-price-data

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Onur Yildirim
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • Computer Systems Machine Learning
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Context This dataset is extracted from the The Boston Housing Dataset, and the extraction of the data is explained in Extract dataset/dataframe from an URL Acknowledgements A Dataset derived from information collected by the U.S. Census Service concerning housing in the area of Boston Mass. Column description: This dataset contains information collected by the U.S Census Service concerning housing in the area of Boston Mass. It was obtained from the StatLib archive (http://lib.stat.cmu.edu/datasets/boston), and has been used extensively throughout the literature to benchmark algorithms. However, these comparisons were primarily done outside of Delve and are thus somewhat suspect. The dataset is small in size with only 506 cases. The data was originally published by Harrison, D. and Rubinfeld, D.L. Hedonic prices and the demand for clean air', J. Environ. Economics Management, vol.5, 81-102, 1978. Variables in order: CRIM per capita crime rate by town ZN proportion of residential land zoned for lots over 25,000 sq.ft. INDUS proportion of non-retail business acres per town CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise) NOX nitric oxides concentration (parts per 10 million) RM average number of rooms per dwelling AGE proportion of owner-occupied units built prior to 1940 DIS weighted distances to five Boston employment centres RAD index of accessibility to radial highways TAX full-value property-tax rate per 10,000 PTRATIO pupil-teacher ratio by town B 1000(Bk - 0.63)2 where Bk is the proportion of blacks by town LSTAT lower status of the population MEDV Median value of owner-occupied homes in 1000's Inspiration I'd like to find it as the base for data exploration in regression way

14 features

MEDV (target)numeric229 unique values
0 missing
CRIMnumeric504 unique values
0 missing
ZNnumeric26 unique values
0 missing
INDUSnumeric76 unique values
0 missing
CHASnumeric2 unique values
0 missing
NOXnumeric81 unique values
0 missing
RMnumeric446 unique values
0 missing
AGEnumeric356 unique values
0 missing
DISnumeric412 unique values
0 missing
RADnumeric9 unique values
0 missing
TAXnumeric66 unique values
0 missing
PTRATIOnumeric46 unique values
0 missing
Bnumeric357 unique values
0 missing
LSTATnumeric455 unique values
0 missing

19 properties

506
Number of instances (rows) of the dataset.
14
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
14
Number of numeric attributes.
0
Number of nominal attributes.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
-3.37
Average class difference between consecutive instances.
0
Percentage of missing values.
0.03
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.

0 tasks

Define a new task