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nomao_seed_0_nrows_2000_nclasses_10_ncols_100_stratify_True

nomao_seed_0_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=0 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
V1numeric18 unique values
0 missing
V2numeric26 unique values
0 missing
V5numeric363 unique values
0 missing
V6numeric411 unique values
0 missing
V7nominal2 unique values
0 missing
V8nominal2 unique values
0 missing
V9numeric5 unique values
0 missing
V10numeric8 unique values
0 missing
V11numeric58 unique values
0 missing
V12numeric39 unique values
0 missing
V13numeric50 unique values
0 missing
V16nominal3 unique values
0 missing
V17numeric4 unique values
0 missing
V18numeric4 unique values
0 missing
V19numeric14 unique values
0 missing
V20numeric17 unique values
0 missing
V21numeric18 unique values
0 missing
V23nominal3 unique values
0 missing
V24nominal3 unique values
0 missing
V25numeric16 unique values
0 missing
V26numeric26 unique values
0 missing
V27numeric246 unique values
0 missing
V28numeric149 unique values
0 missing
V29numeric192 unique values
0 missing
V30numeric191 unique values
0 missing
V32nominal3 unique values
0 missing
V33numeric13 unique values
0 missing
V34numeric24 unique values
0 missing
V35numeric54 unique values
0 missing
V36numeric47 unique values
0 missing
V38numeric60 unique values
0 missing
V39nominal3 unique values
0 missing
V40nominal3 unique values
0 missing
V41numeric3 unique values
0 missing
V42numeric3 unique values
0 missing
V43numeric15 unique values
0 missing
V44numeric11 unique values
0 missing
V45numeric16 unique values
0 missing
V46numeric11 unique values
0 missing
V47nominal3 unique values
0 missing
V48nominal3 unique values
0 missing
V49numeric5 unique values
0 missing
V50numeric6 unique values
0 missing
V51numeric44 unique values
0 missing
V52numeric31 unique values
0 missing
V53numeric41 unique values
0 missing
V55nominal3 unique values
0 missing
V56nominal3 unique values
0 missing
V57numeric36 unique values
0 missing
V58numeric57 unique values
0 missing
V59numeric881 unique values
0 missing
V60numeric689 unique values
0 missing
V61numeric622 unique values
0 missing
V62numeric724 unique values
0 missing
V63nominal3 unique values
0 missing
V64nominal3 unique values
0 missing
V65numeric33 unique values
0 missing
V66numeric53 unique values
0 missing
V67numeric371 unique values
0 missing
V68numeric273 unique values
0 missing
V69numeric397 unique values
0 missing
V71nominal2 unique values
0 missing
V72nominal2 unique values
0 missing
V73numeric4 unique values
0 missing
V74numeric4 unique values
0 missing
V75numeric12 unique values
0 missing
V76numeric13 unique values
0 missing
V78numeric16 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
V90numeric25 unique values
0 missing
V91numeric39 unique values
0 missing
V92nominal3 unique values
0 missing
V93numeric18 unique values
0 missing
V96nominal3 unique values
0 missing
V97numeric94 unique values
0 missing
V98numeric14 unique values
0 missing
V99numeric17 unique values
0 missing
V100nominal3 unique values
0 missing
V101numeric717 unique values
0 missing
V102numeric26 unique values
0 missing
V104nominal2 unique values
0 missing
V105numeric711 unique values
0 missing
V106numeric20 unique values
0 missing
V108nominal2 unique values
0 missing
V109numeric589 unique values
0 missing
V110numeric48 unique values
0 missing
V111numeric67 unique values
0 missing
V112nominal3 unique values
0 missing
V113numeric561 unique values
0 missing
V114numeric39 unique values
0 missing
V115numeric69 unique values
0 missing
V117numeric331 unique values
0 missing
V118numeric240 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
0.58
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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