Data
house_16H

house_16H

active ARFF Publicly available Visibility: public Uploaded 16-06-2022 by Leo Grin
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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 "classification on numerical features" benchmark. Original description: Author: Source: Unknown - Date unknown Please cite: This database was designed on the basis of data provided by US Census Bureau [http://www.census.gov] (under Lookup Access [http://www.census.gov/cdrom/lookup]: Summary Tape File 1). The data were collected as part of the 1990 US census. These are mostly counts cumulated at different survey levels. For the purpose of this data set a level State-Place was used. Data from all states was obtained. Most of the counts were changed into appropriate proportions. There are 4 different data sets obtained from this database: House(8H) House(8L) House(16H) House(16L) These are all concerned with predicting the median price of the house in the region based on demographic composition and a state of housing market in the region. A number in the name signifies the number of attributes of the data set. A following letter denotes a very rough approximation to the difficulty of the task. For Low task difficulty, more correlated attributes were chosen as signified by univariate smooth fit of that input on the target. Tasks with High difficulty have had their attributes chosen to make the modelling more difficult due to higher variance or lower correlation of the inputs to the target. Original source: DELVE repository of data. Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html Characteristics: 22784 cases, 17 continuous attributes.

17 features

price (target)numeric2045 unique values
0 missing
P1numeric8832 unique values
0 missing
P5p1numeric17504 unique values
0 missing
P6p2numeric13683 unique values
0 missing
P11p4numeric19220 unique values
0 missing
P14p9numeric16168 unique values
0 missing
P15p1numeric18753 unique values
0 missing
P15p3numeric9655 unique values
0 missing
P16p2numeric15570 unique values
0 missing
P18p2numeric8070 unique values
0 missing
P27p4numeric12052 unique values
0 missing
H2p2numeric15662 unique values
0 missing
H8p2numeric10941 unique values
0 missing
H10p1numeric10855 unique values
0 missing
H13p1numeric17097 unique values
0 missing
H18pAnumeric9063 unique values
0 missing
H40p4numeric2421 unique values
0 missing

19 properties

22784
Number of instances (rows) of the dataset.
17
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.
17
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0.15
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
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.
0
Number of binary attributes.

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