DEVELOPMENT... OpenML
Data
diamonds

diamonds

active ARFF public domain Visibility: public Uploaded 05-07-2022 by Frank Wallace
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
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: This classic dataset contains the prices and other attributes of almost 54,000 diamonds. It's a great dataset for beginners learning to work with data analysis and visualization. Content price price in US dollars (\$326--\$18,823) carat weight of the diamond (0.2--5.01) cut quality of the cut (Fair, Good, Very Good, Premium, Ideal) color diamond colour, from J (worst) to D (best) clarity a measurement of how clear the diamond is (I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best)) x length in mm (0--10.74) y width in mm (0--58.9) z depth in mm (0--31.8) depth total depth percentage = z / mean(x, y) = 2 * z / (x + y) (43--79) table width of top of diamond relative to widest point (43--95)

7 features

price (target)numeric11602 unique values
0 missing
caratnumeric273 unique values
0 missing
depthnumeric184 unique values
0 missing
tablenumeric127 unique values
0 missing
xnumeric554 unique values
0 missing
ynumeric552 unique values
0 missing
znumeric375 unique values
0 missing

19 properties

53940
Number of instances (rows) of the dataset.
7
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.
7
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of nominal attributes.
0.99
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0
Percentage of missing values.
0
Percentage of instances having missing values.
0
Percentage of binary attributes.
0
Number of binary attributes.
Number of instances belonging to the least frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the most frequent class.
0
Number of attributes divided by the number of instances.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: root_mean_squared_error - target_feature: price
Define a new task