Data
kings_county

kings_county

active ARFF CC 0: Public Domain Visibility: public Uploaded 22-12-2022 by Sebastian Fischer
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  • Agriculture Machine Learning study_353
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Data Description This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. Attribute Description 1. *price* - target feature 2. *bedrooms* - number of bedrooms 3. *bathrooms* - number of bathrooms 4. *sqft_living* - Size of living area in square feet 5. *sqft_lot* - Size of the lot in square feet 6. *floors* - Number of floors 7. *waterfront* - '1' if the property has a waterfront, '0' if not. 8. *view* - an index from 0 to 4 of how good the view of the property was 9. *condition* - Condition of the house, ranked from 1 to 5 10. *grade* - Classification by construction quality which refers to the types of materials used and the quality of workmanship; the higher, the better 11. *sqft_above* - Square feet above ground 12. *sqft_basement* - Square feet below ground 13. *yr_built* - Year built 14. *yr_renovated* - Year renovated. 0 if never renovated 15. *zipcode* - 5 digit zip code 16. *lat* - Latitude 17. *long* - Longitude 18. *sqft_living15* - Average size of interior housing living space for the closest 15 houses, in square feet 19. *sqft_lot15* - Average size of land lots for the closest 15 houses, in square feet 20. *date_year* - Date sold - year 21. *date_month* - Date sold - month 22. *date_day* - Date sold - day

22 features

price (target)numeric4028 unique values
0 missing
bedroomsnumeric13 unique values
0 missing
bathroomsnumeric30 unique values
0 missing
sqft_livingnumeric1038 unique values
0 missing
sqft_lotnumeric9782 unique values
0 missing
floorsnumeric6 unique values
0 missing
waterfrontnumeric2 unique values
0 missing
viewnumeric5 unique values
0 missing
conditionnumeric5 unique values
0 missing
gradenumeric12 unique values
0 missing
sqft_abovenumeric946 unique values
0 missing
sqft_basementnumeric306 unique values
0 missing
yr_builtnumeric116 unique values
0 missing
yr_renovatednumeric70 unique values
0 missing
zipcodenominal70 unique values
0 missing
latnumeric5034 unique values
0 missing
longnumeric752 unique values
0 missing
sqft_living15numeric777 unique values
0 missing
sqft_lot15numeric8689 unique values
0 missing
date_yearnominal2 unique values
0 missing
date_monthnominal12 unique values
0 missing
date_daynominal31 unique values
0 missing

19 properties

21613
Number of instances (rows) of the dataset.
22
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.
18
Number of numeric attributes.
4
Number of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
1
Number of binary attributes.
4.55
Percentage of binary attributes.
0
Percentage of instances having missing values.
-324979.42
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
81.82
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
18.18
Percentage of nominal attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: price
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