OpenML
dataset-autoHorse_fixed

dataset-autoHorse_fixed

active ARFF Public Domain (CC0) Visibility: public Uploaded 18-12-2019 by George Volkov
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
price col is int now. autoHorse dataset

69 features

price (target)numeric186 unique values
0 missing
attribute_0numeric201 unique values
0 missing
symbolingnumeric6 unique values
0 missing
wheel-basenumeric52 unique values
0 missing
lengthnumeric73 unique values
0 missing
widthnumeric43 unique values
0 missing
heightnumeric49 unique values
0 missing
curb-weightnumeric169 unique values
0 missing
num-of-cylindersnumeric7 unique values
0 missing
engine-sizenumeric43 unique values
0 missing
compression-rationumeric32 unique values
0 missing
city-mpgnumeric29 unique values
0 missing
highway-mpgnumeric30 unique values
0 missing
make_alfa-romeronumeric2 unique values
0 missing
make_audinumeric2 unique values
0 missing
make_bmwnumeric2 unique values
0 missing
make_chevroletnumeric2 unique values
0 missing
make_dodgenumeric2 unique values
0 missing
make_hondanumeric2 unique values
0 missing
make_isuzunumeric2 unique values
0 missing
make_jaguarnumeric2 unique values
0 missing
make_mazdanumeric2 unique values
0 missing
make_mercedes-benznumeric2 unique values
0 missing
make_mercurynumeric2 unique values
0 missing
make_mitsubishinumeric2 unique values
0 missing
make_nissannumeric2 unique values
0 missing
make_peugotnumeric2 unique values
0 missing
make_plymouthnumeric2 unique values
0 missing
make_porschenumeric2 unique values
0 missing
make_renaultnumeric2 unique values
0 missing
make_saabnumeric2 unique values
0 missing
make_subarunumeric2 unique values
0 missing
make_toyotanumeric2 unique values
0 missing
make_volkswagennumeric2 unique values
0 missing
make_volvonumeric2 unique values
0 missing
fuel-type_dieselnumeric2 unique values
0 missing
fuel-type_gasnumeric2 unique values
0 missing
aspiration_stdnumeric2 unique values
0 missing
aspiration_turbonumeric2 unique values
0 missing
body-style_convertiblenumeric2 unique values
0 missing
body-style_hardtopnumeric2 unique values
0 missing
body-style_hatchbacknumeric2 unique values
0 missing
body-style_sedannumeric2 unique values
0 missing
body-style_wagonnumeric2 unique values
0 missing
drive-wheels_4wdnumeric2 unique values
0 missing
drive-wheels_fwdnumeric2 unique values
0 missing
drive-wheels_rwdnumeric2 unique values
0 missing
engine-location_frontnumeric2 unique values
0 missing
engine-location_rearnumeric2 unique values
0 missing
engine-type_dohcnumeric2 unique values
0 missing
engine-type_lnumeric2 unique values
0 missing
engine-type_ohcnumeric2 unique values
0 missing
engine-type_ohcfnumeric2 unique values
0 missing
engine-type_ohcvnumeric2 unique values
0 missing
engine-type_rotornumeric2 unique values
0 missing
fuel-system_1bblnumeric2 unique values
0 missing
fuel-system_2bblnumeric2 unique values
0 missing
fuel-system_4bblnumeric2 unique values
0 missing
fuel-system_idinumeric2 unique values
0 missing
fuel-system_mfinumeric2 unique values
0 missing
fuel-system_mpfinumeric2 unique values
0 missing
fuel-system_spdinumeric2 unique values
0 missing
fuel-system_spfinumeric2 unique values
0 missing
normalized-lossesnumeric51 unique values
0 missing
num-of-doorsnumeric3 unique values
0 missing
borenumeric39 unique values
0 missing
strokenumeric37 unique values
0 missing
peak-rpmnumeric23 unique values
0 missing
classnumeric59 unique values
0 missing

19 properties

201
Number of instances (rows) of the dataset.
69
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.
69
Number of numeric attributes.
0
Number of nominal attributes.
0.34
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage 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.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
-2693.33
Average class difference between consecutive instances.
0
Percentage of missing values.

12 tasks

15 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: price
0 runs - estimation_procedure: Custom 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: Test on Training Data - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task