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APSFailure_seed_4_nrows_2000_nclasses_10_ncols_100_stratify_True

APSFailure_seed_4_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=4 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
ad_000numeric503 unique values
495 missing
af_000numeric35 unique values
79 missing
ag_000numeric6 unique values
20 missing
ag_004numeric1497 unique values
20 missing
ag_005numeric1875 unique values
20 missing
ag_007numeric1420 unique values
20 missing
ag_009numeric534 unique values
20 missing
ah_000numeric1948 unique values
21 missing
ak_000numeric10 unique values
143 missing
am_0numeric671 unique values
17 missing
an_000numeric1963 unique values
21 missing
ao_000numeric1964 unique values
16 missing
aq_000numeric1892 unique values
16 missing
as_000numeric3 unique values
17 missing
au_000numeric5 unique values
17 missing
av_000numeric676 unique values
80 missing
ay_000numeric16 unique values
20 missing
ay_001numeric37 unique values
20 missing
ay_003numeric41 unique values
20 missing
ay_004numeric62 unique values
20 missing
ay_005numeric957 unique values
20 missing
ay_009numeric20 unique values
20 missing
az_002numeric1174 unique values
20 missing
az_003numeric1488 unique values
20 missing
az_004numeric1768 unique values
20 missing
az_006numeric1050 unique values
20 missing
az_007numeric213 unique values
20 missing
az_008numeric76 unique values
20 missing
az_009numeric23 unique values
20 missing
ba_000numeric1929 unique values
20 missing
ba_002numeric1768 unique values
20 missing
ba_005numeric1565 unique values
20 missing
ba_006numeric1529 unique values
20 missing
ba_007numeric1326 unique values
20 missing
ba_008numeric732 unique values
20 missing
bb_000numeric1964 unique values
21 missing
bc_000numeric388 unique values
88 missing
bd_000numeric559 unique values
88 missing
bf_000numeric176 unique values
79 missing
bg_000numeric1947 unique values
21 missing
bh_000numeric1669 unique values
21 missing
bj_000numeric1932 unique values
16 missing
bl_000numeric907 unique values
920 missing
bm_000numeric506 unique values
1314 missing
bn_000numeric341 unique values
1473 missing
bo_000numeric264 unique values
1543 missing
bp_000numeric216 unique values
1585 missing
bq_000numeric178 unique values
1618 missing
br_000numeric160 unique values
1634 missing
bt_000numeric1960 unique values
4 missing
bx_000numeric1886 unique values
104 missing
bz_000numeric1180 unique values
88 missing
cb_000numeric1904 unique values
22 missing
cd_000numeric1 unique values
21 missing
ce_000numeric1393 unique values
80 missing
cf_000numeric48 unique values
495 missing
ch_000numeric2 unique values
495 missing
cj_000numeric358 unique values
9 missing
cm_000numeric362 unique values
339 missing
cn_001numeric268 unique values
20 missing
cn_002numeric897 unique values
20 missing
cn_004numeric1915 unique values
20 missing
cn_006numeric1656 unique values
20 missing
cn_008numeric1125 unique values
20 missing
cr_000numeric5 unique values
1547 missing
cs_000numeric1473 unique values
20 missing
cs_002numeric1520 unique values
20 missing
cs_004numeric1817 unique values
20 missing
cs_005numeric1919 unique values
20 missing
cs_007numeric1642 unique values
20 missing
cs_008numeric269 unique values
20 missing
cs_009numeric11 unique values
20 missing
ct_000numeric607 unique values
452 missing
cv_000numeric1491 unique values
452 missing
cy_000numeric98 unique values
452 missing
dd_000numeric1088 unique values
80 missing
de_000numeric430 unique values
88 missing
df_000numeric30 unique values
129 missing
dg_000numeric55 unique values
129 missing
dk_000numeric7 unique values
129 missing
dl_000numeric8 unique values
129 missing
dm_000numeric8 unique values
129 missing
do_000numeric1300 unique values
88 missing
dq_000numeric415 unique values
88 missing
ds_000numeric1585 unique values
88 missing
dt_000numeric1343 unique values
88 missing
dv_000numeric1618 unique values
88 missing
dx_000numeric582 unique values
88 missing
ea_000numeric14 unique values
88 missing
eb_000numeric1138 unique values
129 missing
ec_00numeric1547 unique values
349 missing
ed_000numeric841 unique values
330 missing
ee_000numeric1918 unique values
20 missing
ee_001numeric1907 unique values
20 missing
ee_003numeric1672 unique values
20 missing
ee_004numeric1711 unique values
20 missing
ee_006numeric1584 unique values
20 missing
ee_008numeric1232 unique values
20 missing
ef_000numeric3 unique values
88 missing
eg_000numeric8 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
19156
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
1975
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
9.48
Percentage of missing values.
PercentageOfInstancesWithMissingValues
98.75
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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