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dilbert_seed_1_nrows_2000_nclasses_10_ncols_100_stratify_True

dilbert_seed_1_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 dilbert (41163) with seed=1 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)nominal5 unique values
0 missing
V39numeric1994 unique values
0 missing
V53numeric1998 unique values
0 missing
V67numeric1997 unique values
0 missing
V79numeric1997 unique values
0 missing
V109numeric1997 unique values
0 missing
V121numeric1996 unique values
0 missing
V124numeric1996 unique values
0 missing
V165numeric1995 unique values
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V180numeric1995 unique values
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V228numeric1998 unique values
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V240numeric1998 unique values
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V241numeric1997 unique values
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V260numeric1997 unique values
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V275numeric1998 unique values
0 missing
V296numeric2000 unique values
0 missing
V315numeric1998 unique values
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V395numeric1998 unique values
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V427numeric1997 unique values
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V476numeric1998 unique values
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V493numeric1997 unique values
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V509numeric1999 unique values
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V518numeric1998 unique values
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V523numeric1996 unique values
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V542numeric1997 unique values
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V546numeric1996 unique values
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V573numeric2000 unique values
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V576numeric2000 unique values
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V586numeric1998 unique values
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V596numeric1996 unique values
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V632numeric1998 unique values
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V636numeric1999 unique values
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V686numeric1994 unique values
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V715numeric1999 unique values
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V781numeric1998 unique values
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V810numeric1998 unique values
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V844numeric1993 unique values
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V873numeric1993 unique values
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V877numeric1995 unique values
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V897numeric1991 unique values
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V900numeric1994 unique values
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V906numeric1994 unique values
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V909numeric1993 unique values
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V945numeric1993 unique values
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V970numeric1997 unique values
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V974numeric1997 unique values
0 missing
V1013numeric1993 unique values
0 missing
V1015numeric1991 unique values
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V1019numeric1998 unique values
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V1036numeric1994 unique values
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V1045numeric1992 unique values
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V1055numeric1996 unique values
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V1058numeric1996 unique values
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V1090numeric1998 unique values
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V1235numeric1997 unique values
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V1272numeric1998 unique values
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V1343numeric2000 unique values
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V1415numeric1999 unique values
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V1420numeric1993 unique values
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V1421numeric1996 unique values
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V1438numeric1995 unique values
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V1449numeric1990 unique values
0 missing
V1458numeric1995 unique values
0 missing
V1461numeric2000 unique values
0 missing
V1504numeric1997 unique values
0 missing
V1521numeric1999 unique values
0 missing
V1524numeric1999 unique values
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V1528numeric1996 unique values
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V1529numeric1997 unique values
0 missing
V1570numeric1995 unique values
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V1574numeric1994 unique values
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V1599numeric1992 unique values
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V1612numeric1995 unique values
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V1640numeric1991 unique values
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V1661numeric1996 unique values
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V1663numeric1994 unique values
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V1672numeric1991 unique values
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V1692numeric1995 unique values
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V1725numeric1997 unique values
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V1751numeric2000 unique values
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V1809numeric1994 unique values
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V1810numeric1993 unique values
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V1811numeric1998 unique values
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V1876numeric1998 unique values
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V1889numeric1997 unique values
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V1902numeric1998 unique values
0 missing
V1911numeric1998 unique values
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V1939numeric1994 unique values
0 missing
V1957numeric1998 unique values
0 missing
V1964numeric1996 unique values
0 missing
V1972numeric1998 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
5
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
100
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
PercentageOfSymbolicFeatures
0.99
Percentage of nominal attributes.
AutoCorrelation
0.2
Average class difference between consecutive instances.
PercentageOfNumericFeatures
99.01
Percentage of numeric attributes.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
NumberOfBinaryFeatures
0
Number of binary attributes.
MinorityClassSize
383
Number of instances belonging to the least frequent class.
MinorityClassPercentage
19.15
Percentage of instances belonging to the least frequent class.
MajorityClassSize
410
Number of instances belonging to the most frequent class.
MajorityClassPercentage
20.5
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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