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albert_seed_4_nrows_2000_nclasses_10_ncols_100_stratify_True

albert_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 albert (41147) 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, ) ```

79 features

class (target)nominal2 unique values
0 missing
V59numeric151 unique values
91 missing
V41nominal4 unique values
0 missing
V58nominal810 unique values
0 missing
V57nominal648 unique values
0 missing
V56nominal1048 unique values
0 missing
V55nominal1428 unique values
0 missing
V54nominal238 unique values
0 missing
V53numeric25 unique values
1514 missing
V52numeric6 unique values
784 missing
V51numeric45 unique values
86 missing
V50numeric144 unique values
84 missing
V49nominal250 unique values
0 missing
V48nominal29 unique values
0 missing
V47nominal7 unique values
0 missing
V46nominal1176 unique values
0 missing
V45nominal9 unique values
0 missing
V44nominal1271 unique values
0 missing
V43numeric339 unique values
345 missing
V42numeric51 unique values
2 missing
V40numeric154 unique values
85 missing
V69numeric20 unique values
1513 missing
V78nominal806 unique values
0 missing
V77nominal879 unique values
0 missing
V76nominal30 unique values
0 missing
V75numeric41 unique values
56 missing
V74nominal29 unique values
0 missing
V73nominal31 unique values
0 missing
V72numeric43 unique values
64 missing
V71nominal34 unique values
0 missing
V70nominal26 unique values
0 missing
V60nominal252 unique values
0 missing
V68nominal18 unique values
0 missing
V67numeric21 unique values
1504 missing
V66nominal1166 unique values
0 missing
V65nominal18 unique values
0 missing
V64numeric19 unique values
1490 missing
V63nominal12 unique values
0 missing
V62nominal799 unique values
0 missing
V61nominal820 unique values
0 missing
V11numeric38 unique values
67 missing
V20nominal1187 unique values
0 missing
V19nominal8 unique values
0 missing
V18nominal33 unique values
0 missing
V17nominal1148 unique values
0 missing
V16nominal1417 unique values
0 missing
V15nominal251 unique values
0 missing
V14nominal73 unique values
0 missing
V13numeric58 unique values
458 missing
V12numeric17 unique values
1523 missing
V21nominal43 unique values
0 missing
V10numeric6 unique values
792 missing
V9numeric414 unique values
67 missing
V8numeric51 unique values
1 missing
V7numeric158 unique values
67 missing
V6numeric337 unique values
348 missing
V5numeric1437 unique values
34 missing
V4numeric52 unique values
458 missing
V3numeric122 unique values
472 missing
V2numeric361 unique values
0 missing
V30nominal9 unique values
0 missing
V39nominal641 unique values
0 missing
V38nominal31 unique values
0 missing
V37nominal830 unique values
0 missing
V36nominal12 unique values
0 missing
V35nominal7 unique values
0 missing
V34nominal1331 unique values
0 missing
V33nominal4 unique values
0 missing
V32nominal214 unique values
0 missing
V31nominal565 unique values
0 missing
V1numeric45 unique values
792 missing
V29nominal1279 unique values
0 missing
V28nominal884 unique values
0 missing
V27nominal16 unique values
0 missing
V26nominal805 unique values
0 missing
V25nominal1367 unique values
0 missing
V24nominal911 unique values
0 missing
V23nominal1104 unique values
0 missing
V22nominal3 unique values
0 missing
Show all 79 features

19 properties

NumberOfInstances
2000
Number of instances (rows) of the dataset.
NumberOfFeatures
79
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
12697
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
2000
Number of instances with at least one value missing.
NumberOfNumericFeatures
26
Number of numeric attributes.
NumberOfSymbolicFeatures
53
Number of nominal attributes.
PercentageOfSymbolicFeatures
67.09
Percentage of nominal attributes.
AutoCorrelation
0.5
Average class difference between consecutive instances.
PercentageOfNumericFeatures
32.91
Percentage of numeric attributes.
PercentageOfMissingValues
8.04
Percentage of missing values.
PercentageOfInstancesWithMissingValues
100
Percentage of instances having missing values.
PercentageOfBinaryFeatures
1.27
Percentage of binary attributes.
NumberOfBinaryFeatures
1
Number of binary attributes.
MinorityClassSize
1000
Number of instances belonging to the least frequent class.
MinorityClassPercentage
50
Percentage of instances belonging to the least frequent class.
MajorityClassSize
1000
Number of instances belonging to the most frequent class.
MajorityClassPercentage
50
Percentage of instances belonging to the most frequent class.
Dimensionality
0.04
Number of attributes divided by the number of instances.
Show all 19 properties

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