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APSFailure_seed_2_nrows_2000_nclasses_10_ncols_100_stratify_True

APSFailure_seed_2_nrows_2000_nclasses_10_ncols_100_stratify_True

active ARFF Public Domain (CC0) Visibility: public Uploaded 17-11-2022 by David Wilson
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Subsampling of the dataset APSFailure (41138) with seed=2 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self, seed: int, nrows_max: int = 2_000, ncols_max: int = 100, nclasses_max: int = 10, stratified: bool = True, ) -> Dataset: rng = np.random.default_rng(seed) x = self.x y = self.y # Uniformly sample classes = y.unique() if len(classes) > nclasses_max: vcs = y.value_counts() selected_classes = rng.choice( classes, size=nclasses_max, replace=False, p=vcs / sum(vcs), ) # Select the indices where one of these classes is present idxs = y.index[y.isin(classes)] x = x.iloc[idxs] y = y.iloc[idxs] # Uniformly sample columns if required if len(x.columns) > ncols_max: columns_idxs = rng.choice( list(range(len(x.columns))), size=ncols_max, replace=False ) sorted_column_idxs = sorted(columns_idxs) selected_columns = list(x.columns[sorted_column_idxs]) x = x[selected_columns] else: sorted_column_idxs = list(range(len(x.columns))) if len(x) > nrows_max: # Stratify accordingly target_name = y.name data = pd.concat((x, y), axis="columns") _, subset = train_test_split( data, test_size=nrows_max, stratify=data[target_name], shuffle=True, random_state=seed, ) x = subset.drop(target_name, axis="columns") y = subset[target_name] # We need to convert categorical columns to string for openml categorical_mask = [self.categorical_mask[i] for i in sorted_column_idxs] columns = list(x.columns) return Dataset( # Technically this is not the same but it's where it was derived from dataset=self.dataset, x=x, y=y, categorical_mask=categorical_mask, columns=columns, ) ```

101 features

class (target)nominal2 unique values
0 missing
ae_000numeric38 unique values
80 missing
ag_000numeric3 unique values
14 missing
ag_001numeric26 unique values
14 missing
ag_003numeric413 unique values
14 missing
ag_005numeric1887 unique values
14 missing
ag_007numeric1437 unique values
14 missing
ag_008numeric1097 unique values
14 missing
ag_009numeric528 unique values
14 missing
ah_000numeric1958 unique values
12 missing
ai_000numeric192 unique values
11 missing
aj_000numeric177 unique values
11 missing
al_000numeric682 unique values
12 missing
an_000numeric1971 unique values
12 missing
ap_000numeric1968 unique values
12 missing
ar_000numeric18 unique values
88 missing
as_000numeric1 unique values
11 missing
ax_000numeric440 unique values
80 missing
ay_002numeric36 unique values
14 missing
ay_003numeric38 unique values
14 missing
ay_004numeric65 unique values
14 missing
ay_006numeric1414 unique values
14 missing
ay_008numeric1758 unique values
14 missing
ay_009numeric17 unique values
14 missing
az_000numeric1414 unique values
14 missing
az_001numeric1050 unique values
14 missing
az_006numeric1031 unique values
14 missing
az_009numeric28 unique values
14 missing
ba_002numeric1786 unique values
14 missing
ba_005numeric1588 unique values
14 missing
ba_006numeric1548 unique values
14 missing
ba_007numeric1343 unique values
14 missing
ba_009numeric420 unique values
14 missing
bc_000numeric383 unique values
88 missing
bd_000numeric559 unique values
88 missing
be_000numeric675 unique values
80 missing
bg_000numeric1958 unique values
12 missing
bh_000numeric1699 unique values
12 missing
bi_000numeric1959 unique values
10 missing
bj_000numeric1941 unique values
10 missing
bk_000numeric1096 unique values
770 missing
bl_000numeric922 unique values
914 missing
bm_000numeric536 unique values
1307 missing
bn_000numeric365 unique values
1461 missing
bq_000numeric196 unique values
1608 missing
br_000numeric166 unique values
1634 missing
bs_000numeric1730 unique values
18 missing
bu_000numeric1973 unique values
12 missing
bv_000numeric1973 unique values
12 missing
by_000numeric1583 unique values
8 missing
bz_000numeric1171 unique values
88 missing
ca_000numeric1782 unique values
146 missing
cb_000numeric1926 unique values
18 missing
cc_000numeric1847 unique values
109 missing
cd_000numeric1 unique values
13 missing
ce_000numeric1394 unique values
80 missing
cf_000numeric50 unique values
488 missing
cg_000numeric183 unique values
488 missing
ch_000numeric1 unique values
488 missing
ci_000numeric1973 unique values
7 missing
ck_000numeric1970 unique values
7 missing
cl_000numeric132 unique values
316 missing
cn_001numeric300 unique values
14 missing
cn_002numeric921 unique values
14 missing
cn_003numeric1839 unique values
14 missing
cn_004numeric1912 unique values
14 missing
cn_008numeric1154 unique values
14 missing
cn_009numeric524 unique values
14 missing
co_000numeric298 unique values
488 missing
cp_000numeric346 unique values
88 missing
cr_000numeric6 unique values
1530 missing
cs_000numeric1511 unique values
14 missing
cs_002numeric1530 unique values
14 missing
cs_003numeric1761 unique values
14 missing
cs_004numeric1834 unique values
14 missing
cs_005numeric1919 unique values
14 missing
cs_006numeric1907 unique values
14 missing
cs_008numeric279 unique values
14 missing
cs_009numeric11 unique values
14 missing
ct_000numeric605 unique values
445 missing
cu_000numeric677 unique values
445 missing
cv_000numeric1495 unique values
445 missing
cy_000numeric97 unique values
445 missing
cz_000numeric802 unique values
445 missing
da_000numeric23 unique values
445 missing
dc_000numeric1497 unique values
445 missing
dd_000numeric1141 unique values
80 missing
de_000numeric455 unique values
88 missing
dg_000numeric46 unique values
137 missing
di_000numeric298 unique values
137 missing
dj_000numeric8 unique values
137 missing
do_000numeric1270 unique values
88 missing
dq_000numeric415 unique values
88 missing
dt_000numeric1339 unique values
88 missing
du_000numeric1570 unique values
88 missing
dx_000numeric565 unique values
88 missing
eb_000numeric1151 unique values
137 missing
ec_00numeric1563 unique values
338 missing
ee_000numeric1924 unique values
14 missing
ee_004numeric1705 unique values
14 missing
ef_000numeric4 unique values
88 missing
Show first 100 features

19 properties

NumberOfInstances
2000
Number of instances (rows) of the dataset.
NumberOfFeatures
101
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
17956
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
1985
Number of instances with at least one value missing.
NumberOfNumericFeatures
100
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
PercentageOfSymbolicFeatures
0.99
Percentage of nominal attributes.
AutoCorrelation
0.96
Average class difference between consecutive instances.
PercentageOfNumericFeatures
99.01
Percentage of numeric attributes.
PercentageOfMissingValues
8.89
Percentage of missing values.
PercentageOfInstancesWithMissingValues
99.25
Percentage of instances having missing values.
PercentageOfBinaryFeatures
0.99
Percentage of binary attributes.
NumberOfBinaryFeatures
1
Number of binary attributes.
MinorityClassSize
36
Number of instances belonging to the least frequent class.
MinorityClassPercentage
1.8
Percentage of instances belonging to the least frequent class.
MajorityClassSize
1964
Number of instances belonging to the most frequent class.
MajorityClassPercentage
98.2
Percentage of instances belonging to the most frequent class.
Dimensionality
0.05
Number of attributes divided by the number of instances.
Show all 19 properties

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