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guillermo_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 guillermo (41159) 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)	nominal	2 unique values 0 missing
V84	numeric	782 unique values 0 missing
V117	numeric	488 unique values 0 missing
V147	numeric	239 unique values 0 missing
V170	numeric	180 unique values 0 missing
V233	numeric	540 unique values 0 missing
V263	numeric	603 unique values 0 missing
V267	numeric	613 unique values 0 missing
V362	numeric	628 unique values 0 missing
V392	numeric	1 unique values 0 missing
V494	numeric	678 unique values 0 missing
V497	numeric	662 unique values 0 missing
V524	numeric	367 unique values 0 missing
V526	numeric	454 unique values 0 missing
V567	numeric	697 unique values 0 missing
V606	numeric	680 unique values 0 missing
V636	numeric	267 unique values 0 missing
V684	numeric	507 unique values 0 missing
V862	numeric	676 unique values 0 missing
V920	numeric	306 unique values 0 missing
V1049	numeric	406 unique values 0 missing
V1083	numeric	412 unique values 0 missing
V1112	numeric	329 unique values 0 missing
V1115	numeric	718 unique values 0 missing
V1150	numeric	499 unique values 0 missing
V1178	numeric	357 unique values 0 missing
V1189	numeric	178 unique values 0 missing
V1246	numeric	350 unique values 0 missing
V1248	numeric	548 unique values 0 missing
V1282	numeric	391 unique values 0 missing
V1312	numeric	738 unique values 0 missing
V1373	numeric	474 unique values 0 missing
V1393	numeric	903 unique values 0 missing
V1477	numeric	551 unique values 0 missing
V1548	numeric	772 unique values 0 missing
V1574	numeric	731 unique values 0 missing
V1622	numeric	338 unique values 0 missing
V1706	numeric	359 unique values 0 missing
V1724	numeric	646 unique values 0 missing
V1782	numeric	700 unique values 0 missing
V1793	numeric	674 unique values 0 missing
V1810	numeric	606 unique values 0 missing
V1825	numeric	712 unique values 0 missing
V1912	numeric	574 unique values 0 missing
V1918	numeric	534 unique values 0 missing
V1943	numeric	546 unique values 0 missing
V1956	numeric	586 unique values 0 missing
V1964	numeric	959 unique values 0 missing
V1986	numeric	781 unique values 0 missing
V2059	numeric	619 unique values 0 missing
V2114	numeric	639 unique values 0 missing
V2128	numeric	464 unique values 0 missing
V2149	numeric	834 unique values 0 missing
V2185	numeric	1 unique values 0 missing
V2192	numeric	864 unique values 0 missing
V2198	numeric	808 unique values 0 missing
V2259	numeric	139 unique values 0 missing
V2271	numeric	641 unique values 0 missing
V2301	numeric	271 unique values 0 missing
V2316	numeric	195 unique values 0 missing
V2342	numeric	653 unique values 0 missing
V2494	numeric	737 unique values 0 missing
V2539	numeric	465 unique values 0 missing
V2616	numeric	588 unique values 0 missing
V2658	numeric	478 unique values 0 missing
V2713	numeric	577 unique values 0 missing
V2744	numeric	437 unique values 0 missing
V2890	numeric	470 unique values 0 missing
V3069	numeric	268 unique values 0 missing
V3079	numeric	353 unique values 0 missing
V3088	numeric	732 unique values 0 missing
V3171	numeric	292 unique values 0 missing
V3179	numeric	589 unique values 0 missing
V3180	numeric	839 unique values 0 missing
V3181	numeric	801 unique values 0 missing
V3233	numeric	755 unique values 0 missing
V3296	numeric	189 unique values 0 missing
V3298	numeric	330 unique values 0 missing
V3312	numeric	757 unique values 0 missing
V3331	numeric	815 unique values 0 missing
V3446	numeric	465 unique values 0 missing
V3451	numeric	698 unique values 0 missing
V3459	numeric	857 unique values 0 missing
V3485	numeric	882 unique values 0 missing
V3522	numeric	618 unique values 0 missing
V3536	numeric	799 unique values 0 missing
V3600	numeric	804 unique values 0 missing
V3650	numeric	555 unique values 0 missing
V3651	numeric	537 unique values 0 missing
V3656	numeric	435 unique values 0 missing
V3727	numeric	585 unique values 0 missing
V3827	numeric	411 unique values 0 missing
V3916	numeric	366 unique values 0 missing
V3932	numeric	647 unique values 0 missing
V3989	numeric	347 unique values 0 missing
V3992	numeric	762 unique values 0 missing
V4084	numeric	627 unique values 0 missing
V4129	numeric	1240 unique values 0 missing
V4132	numeric	1243 unique values 0 missing
V4163	numeric	1238 unique values 0 missing
V4210	numeric	1240 unique values 0 missing