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nomao_seed_4_nrows_2000_nclasses_10_ncols_100_stratify_True

nomao_seed_4_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=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
V3numeric587 unique values
0 missing
V5numeric379 unique values
0 missing
V6numeric430 unique values
0 missing
V7nominal2 unique values
0 missing
V9numeric5 unique values
0 missing
V10numeric9 unique values
0 missing
V11numeric49 unique values
0 missing
V12numeric34 unique values
0 missing
V13numeric43 unique values
0 missing
V14numeric34 unique values
0 missing
V15nominal3 unique values
0 missing
V16nominal3 unique values
0 missing
V18numeric4 unique values
0 missing
V19numeric12 unique values
0 missing
V20numeric12 unique values
0 missing
V21numeric13 unique values
0 missing
V22numeric13 unique values
0 missing
V24nominal3 unique values
0 missing
V25numeric17 unique values
0 missing
V26numeric27 unique values
0 missing
V27numeric253 unique values
0 missing
V30numeric205 unique values
0 missing
V31nominal3 unique values
0 missing
V32nominal3 unique values
0 missing
V33numeric12 unique values
0 missing
V34numeric23 unique values
0 missing
V35numeric54 unique values
0 missing
V36numeric47 unique values
0 missing
V37numeric52 unique values
0 missing
V38numeric58 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
V46numeric11 unique values
0 missing
V47nominal3 unique values
0 missing
V48nominal3 unique values
0 missing
V49numeric4 unique values
0 missing
V50numeric5 unique values
0 missing
V51numeric37 unique values
0 missing
V52numeric21 unique values
0 missing
V53numeric29 unique values
0 missing
V54numeric21 unique values
0 missing
V55nominal3 unique values
0 missing
V56nominal3 unique values
0 missing
V59numeric880 unique values
0 missing
V60numeric697 unique values
0 missing
V61numeric637 unique values
0 missing
V62numeric736 unique values
0 missing
V63nominal3 unique values
0 missing
V64nominal3 unique values
0 missing
V65numeric30 unique values
0 missing
V66numeric50 unique values
0 missing
V67numeric377 unique values
0 missing
V69numeric396 unique values
0 missing
V70numeric443 unique values
0 missing
V71nominal2 unique values
0 missing
V72nominal2 unique values
0 missing
V73numeric4 unique values
0 missing
V74numeric4 unique values
0 missing
V75numeric14 unique values
0 missing
V76numeric14 unique values
0 missing
V78numeric14 unique values
0 missing
V79nominal3 unique values
0 missing
V80nominal3 unique values
0 missing
V81numeric3 unique values
0 missing
V83numeric3 unique values
0 missing
V84numeric3 unique values
0 missing
V85numeric3 unique values
0 missing
V86numeric3 unique values
0 missing
V87nominal3 unique values
0 missing
V88nominal3 unique values
0 missing
V89numeric113 unique values
0 missing
V90numeric27 unique values
0 missing
V91numeric36 unique values
0 missing
V92nominal3 unique values
0 missing
V93numeric20 unique values
0 missing
V94numeric16 unique values
0 missing
V96nominal3 unique values
0 missing
V97numeric92 unique values
0 missing
V98numeric13 unique values
0 missing
V99numeric15 unique values
0 missing
V100nominal3 unique values
0 missing
V101numeric739 unique values
0 missing
V102numeric28 unique values
0 missing
V103numeric40 unique values
0 missing
V104nominal2 unique values
0 missing
V105numeric707 unique values
0 missing
V106numeric21 unique values
0 missing
V107numeric45 unique values
0 missing
V108nominal2 unique values
0 missing
V109numeric601 unique values
0 missing
V110numeric45 unique values
0 missing
V111numeric69 unique values
0 missing
V112nominal3 unique values
0 missing
V113numeric549 unique values
0 missing
V114numeric38 unique values
0 missing
V118numeric231 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
74
Number of numeric attributes.
NumberOfSymbolicFeatures
27
Number of nominal attributes.
PercentageOfSymbolicFeatures
26.73
Percentage of nominal attributes.
AutoCorrelation
0.6
Average class difference between consecutive instances.
PercentageOfNumericFeatures
73.27
Percentage of numeric attributes.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfBinaryFeatures
1.98
Percentage of binary attributes.
NumberOfBinaryFeatures
2
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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