Data
California-Housing-Classification

California-Housing-Classification

active ARFF Publicly available Visibility: public Uploaded 20-06-2023 by Matthias Feurer
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Binarized version of the California Housing Dataset This dataset was obtained from Luis Torgo's collection of regression datasets. It was binarized to serve as the original, unprocessed date for the California Housing dataset used by: > Grinsztajn, Leo and Oyallon, Edouard and Varoquaux, Gael > Why do tree-based models still outperform deep learning on typical tabular data? > In: Advances in Neural Information Processing Systems (2022) ## Description: This is a dataset obtained from the StatLib repository. Here is the included description: S&P Letters Data We collected information on the variables using all the block groups in California from the 1990 Cens us. In this sample a block group on average includes 1425.5 individuals living in a geographically co mpact area. Naturally, the geographical area included varies inversely with the population density. W e computed distances among the centroids of each block group as measured in latitude and longitude. W e excluded all the block groups reporting zero entries for the independent and dependent variables. T he final data contained 20,640 observations on 9 variables. The dependent variable is ln(median house value). | | Bols | tols | |-----------------------------|----------|----------| | INTERCEPT | 11.4939 | 275.7518 | | MEDIAN INCOME | 0.4790 | 45.7768 | | MEDIAN INCOME2 | -0.0166 | -9.4841 | | MEDIAN INCOME3 | -0.0002 | -1.9157 | | ln(MEDIAN AGE) | 0.1570 | 33.6123 | | ln(TOTAL ROOMS/ POPULATION) | -0.8582 | -56.1280 | | ln(BEDROOMS/ POPULATION) | 0.8043 | 38.0685 | | ln(POPULATION/ HOUSEHOLDS) | -0.4077 | -20.8762 | | ln(HOUSEHOLDS) | 0.0477 | 13.0792 | The file contains all the the variables. Specifically, it contains median house value, med ian income, housing median age, total rooms, total bedrooms, population, households, latitude, and lo ngitude in that order. Reference Pace, R. Kelley and Ronald Barry, Sparse Spatial Autoregressions, Statistics and Probability Letters, 33 (1997) 291-297. The manuscript describing the data can be found at www.spatial-statistics.com. The data are also available as Matlab files. Contact kelley@spatial-statistics.com or kelley@pace.am if you have any further questions. Thanks.

9 features

medianHouseValue (target)nominal2 unique values
0 missing
longitudenumeric844 unique values
0 missing
latitudenumeric862 unique values
0 missing
housingMedianAgenumeric52 unique values
0 missing
totalRoomsnumeric5926 unique values
0 missing
totalBedroomsnumeric1928 unique values
0 missing
populationnumeric3888 unique values
0 missing
householdsnumeric1815 unique values
0 missing
medianIncomenumeric12928 unique values
0 missing

19 properties

20640
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
2
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.
8
Number of numeric attributes.
1
Number of nominal attributes.
11.11
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.87
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
88.89
Percentage of numeric attributes.
50.01
Percentage of instances belonging to the most frequent class.
11.11
Percentage of nominal attributes.
10323
Number of instances belonging to the most frequent class.
49.99
Percentage of instances belonging to the least frequent class.
10317
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: medianHouseValue
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