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house_sales

house_sales

active ARFF CC0 Public Domain Visibility: public Uploaded 05-07-2022 by Frank Wallace
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Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on numerical features" benchmark. Original description: Date converted to year/mo/day numerics.This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. It contains 19 house features plus the price and the id columns, along with 21613 observations. It's a great dataset for evaluating simple regression models.

16 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
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
latnumeric5034 unique values
0 missing
longnumeric752 unique values
0 missing
sqft_living15numeric777 unique values
0 missing
sqft_lot15numeric8689 unique values
0 missing
date_monthnumeric12 unique values
0 missing
date_daynumeric31 unique values
0 missing
Show all 16 features

19 properties

NumberOfInstances
21613
Number of instances (rows) of the dataset.
NumberOfFeatures
16
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
16
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
AutoCorrelation
0.42
Average class difference between consecutive instances.
PercentageOfNumericFeatures
100
Percentage of numeric attributes.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
NumberOfBinaryFeatures
0
Number of binary attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
Dimensionality
0
Number of attributes divided by the number of instances.
Show all 19 properties

1 tasks

Supervised Regression on house_sales
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: root_mean_squared_error - target_feature: price
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