Data
mabbob_ela_as_5d_regression_DiagonalCMA

mabbob_ela_as_5d_regression_DiagonalCMA

active ARFF CC-BY Visibility: public Uploaded 10-07-2024 by Olaf Mersmann
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
Algorithm performane prediction problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.

46 features

DiagonalCMA (target)numeric1120 unique values
0 missing
ela_meta.lin_simple.adj_r2numeric1120 unique values
0 missing
ela_meta.lin_simple.interceptnumeric1120 unique values
0 missing
ela_meta.lin_simple.coef.minnumeric1120 unique values
0 missing
ela_meta.lin_simple.coef.maxnumeric1120 unique values
0 missing
ela_meta.lin_simple.coef.max_by_minnumeric1120 unique values
0 missing
ela_meta.lin_w_interact.adj_r2numeric1120 unique values
0 missing
ela_meta.quad_simple.adj_r2numeric1120 unique values
0 missing
ela_meta.quad_simple.condnumeric1120 unique values
0 missing
ela_meta.quad_w_interact.adj_r2numeric1120 unique values
0 missing
ela_distr.skewnessnumeric1120 unique values
0 missing
ela_distr.kurtosisnumeric1120 unique values
0 missing
ela_distr.number_of_peaksnumeric25 unique values
0 missing
ela_level.mmce_lda_10numeric821 unique values
0 missing
ela_level.mmce_qda_10numeric890 unique values
0 missing
ela_level.lda_qda_10numeric1095 unique values
0 missing
ela_level.mmce_lda_25numeric985 unique values
0 missing
ela_level.mmce_qda_25numeric981 unique values
0 missing
ela_level.lda_qda_25numeric1110 unique values
0 missing
ela_level.mmce_lda_50numeric1050 unique values
0 missing
ela_level.mmce_qda_50numeric1011 unique values
0 missing
ela_level.lda_qda_50numeric1119 unique values
0 missing
nbc.nn_nb.sd_rationumeric1120 unique values
0 missing
nbc.nn_nb.mean_rationumeric1120 unique values
0 missing
nbc.nn_nb.cornumeric1120 unique values
0 missing
nbc.dist_ratio.coeff_varnumeric1120 unique values
0 missing
nbc.nb_fitness.cornumeric1120 unique values
0 missing
disp.ratio_mean_02numeric1120 unique values
0 missing
disp.ratio_mean_05numeric1120 unique values
0 missing
disp.ratio_mean_10numeric1120 unique values
0 missing
disp.ratio_mean_25numeric1120 unique values
0 missing
disp.ratio_median_02numeric1120 unique values
0 missing
disp.ratio_median_05numeric1120 unique values
0 missing
disp.ratio_median_10numeric1120 unique values
0 missing
disp.ratio_median_25numeric1120 unique values
0 missing
disp.diff_mean_02numeric1120 unique values
0 missing
disp.diff_mean_05numeric1120 unique values
0 missing
disp.diff_mean_10numeric1120 unique values
0 missing
disp.diff_mean_25numeric1120 unique values
0 missing
disp.diff_median_02numeric1120 unique values
0 missing
disp.diff_median_05numeric1120 unique values
0 missing
disp.diff_median_10numeric1120 unique values
0 missing
disp.diff_median_25numeric1120 unique values
0 missing
ic.h_maxnumeric1120 unique values
0 missing
ic.eps_snumeric216 unique values
0 missing
ic.m0numeric948 unique values
0 missing

19 properties

1120
Number of instances (rows) of the dataset.
46
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.
46
Number of numeric attributes.
0
Number of nominal attributes.
0.71
Average class difference between consecutive instances.
0
Percentage of missing values.
0.04
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.

0 tasks

Define a new task