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nomao_seed_2_nrows_2000_nclasses_10_ncols_100_stratify_True

nomao_seed_2_nrows_2000_nclasses_10_ncols_100_stratify_True

active ARFF Publicly available Visibility: public Uploaded 17-11-2022 by David Wilson
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Subsampling of the dataset nomao (1486) 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
V2numeric30 unique values
0 missing
V3numeric576 unique values
0 missing
V5numeric357 unique values
0 missing
V6numeric399 unique values
0 missing
V7nominal2 unique values
0 missing
V8nominal2 unique values
0 missing
V9numeric7 unique values
0 missing
V10numeric8 unique values
0 missing
V11numeric61 unique values
0 missing
V12numeric42 unique values
0 missing
V16nominal3 unique values
0 missing
V17numeric4 unique values
0 missing
V20numeric17 unique values
0 missing
V21numeric18 unique values
0 missing
V22numeric19 unique values
0 missing
V23nominal3 unique values
0 missing
V24nominal3 unique values
0 missing
V25numeric16 unique values
0 missing
V26numeric24 unique values
0 missing
V27numeric237 unique values
0 missing
V30numeric218 unique values
0 missing
V31nominal3 unique values
0 missing
V32nominal3 unique values
0 missing
V33numeric12 unique values
0 missing
V34numeric21 unique values
0 missing
V35numeric55 unique values
0 missing
V36numeric44 unique values
0 missing
V37numeric47 unique values
0 missing
V38numeric58 unique values
0 missing
V39nominal3 unique values
0 missing
V41numeric3 unique values
0 missing
V42numeric3 unique values
0 missing
V43numeric13 unique values
0 missing
V44numeric9 unique values
0 missing
V45numeric13 unique values
0 missing
V46numeric9 unique values
0 missing
V47nominal3 unique values
0 missing
V48nominal3 unique values
0 missing
V49numeric6 unique values
0 missing
V50numeric6 unique values
0 missing
V51numeric50 unique values
0 missing
V52numeric24 unique values
0 missing
V53numeric37 unique values
0 missing
V55nominal3 unique values
0 missing
V56nominal3 unique values
0 missing
V57numeric39 unique values
0 missing
V58numeric58 unique values
0 missing
V59numeric862 unique values
0 missing
V60numeric686 unique values
0 missing
V61numeric641 unique values
0 missing
V62numeric766 unique values
0 missing
V63nominal3 unique values
0 missing
V64nominal3 unique values
0 missing
V65numeric31 unique values
0 missing
V66numeric51 unique values
0 missing
V68numeric275 unique values
0 missing
V69numeric391 unique values
0 missing
V70numeric439 unique values
0 missing
V71nominal3 unique values
0 missing
V73numeric4 unique values
0 missing
V74numeric4 unique values
0 missing
V75numeric16 unique values
0 missing
V76numeric14 unique values
0 missing
V77numeric16 unique values
0 missing
V78numeric17 unique values
0 missing
V80nominal3 unique values
0 missing
V81numeric2 unique values
0 missing
V82numeric2 unique values
0 missing
V83numeric2 unique values
0 missing
V84numeric2 unique values
0 missing
V86numeric2 unique values
0 missing
V87nominal2 unique values
0 missing
V88nominal2 unique values
0 missing
V90numeric27 unique values
0 missing
V91numeric39 unique values
0 missing
V92nominal3 unique values
0 missing
V93numeric11 unique values
0 missing
V94numeric11 unique values
0 missing
V95numeric11 unique values
0 missing
V96nominal3 unique values
0 missing
V97numeric90 unique values
0 missing
V98numeric14 unique values
0 missing
V99numeric17 unique values
0 missing
V100nominal3 unique values
0 missing
V101numeric723 unique values
0 missing
V102numeric28 unique values
0 missing
V103numeric40 unique values
0 missing
V104nominal3 unique values
0 missing
V105numeric694 unique values
0 missing
V106numeric21 unique values
0 missing
V107numeric48 unique values
0 missing
V108nominal3 unique values
0 missing
V109numeric587 unique values
0 missing
V111numeric66 unique values
0 missing
V112nominal3 unique values
0 missing
V113numeric564 unique values
0 missing
V114numeric41 unique values
0 missing
V115numeric65 unique values
0 missing
V116nominal3 unique values
0 missing
V117numeric314 unique values
0 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
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
75
Number of numeric attributes.
NumberOfSymbolicFeatures
26
Number of nominal attributes.
PercentageOfSymbolicFeatures
25.74
Percentage of nominal attributes.
AutoCorrelation
0.6
Average class difference between consecutive instances.
PercentageOfNumericFeatures
74.26
Percentage of numeric attributes.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfBinaryFeatures
2.97
Percentage of binary attributes.
NumberOfBinaryFeatures
3
Number of binary attributes.
MinorityClassSize
571
Number of instances belonging to the least frequent class.
MinorityClassPercentage
28.55
Percentage of instances belonging to the least frequent class.
MajorityClassSize
1429
Number of instances belonging to the most frequent class.
MajorityClassPercentage
71.45
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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