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Update config
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‎configs/throughput/example.json‎

Lines changed: 202 additions & 42 deletions
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{
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"INCLUDE": ["../common/sklearn.json"],
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"PARAMETERS_SETS": {
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"common parameters": {
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"data": {
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"split_kwargs": {
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"train_size": 8000,
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"test_size": 2000,
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"shuffle": true,
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"throughput settings": {
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"bench": {
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"num_instances": 7,
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"cores_per_instance": 8,
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"measurement_duration": 30
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}
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},
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"linear regression": {
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"algorithm": {
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"estimator": "LinearRegression",
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"estimator_params": {
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"fit_intercept": true,
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"copy_X": true
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}
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}
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},
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"random forest regressor": {
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"algorithm": {
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"estimator": "RandomForestRegressor",
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"estimator_params": {
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"n_estimators": 100,
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"max_depth": 12,
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"random_state": 42
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}
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}
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},
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"knn classifier kdtree": {
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"algorithm": {
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"estimator": "KNeighborsClassifier",
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"estimator_params": {
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"n_neighbors": 10,
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"weights": "uniform",
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"algorithm": "kd_tree",
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"metric": "minkowski",
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"p": 2
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}
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},
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"algorithm": { "device": "default" }
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"data": {
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"preprocessing_kwargs": { "normalize": "standard" }
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}
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},
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"throughput settings": {
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"bench": {
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"num_instances": 4,
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"cores_per_instance": 4,
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"measurement_duration": 30
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"kmeans": {
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"algorithm": {
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"estimator": "KMeans",
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"estimator_params": {
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"n_clusters": 10,
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"n_init": 1,
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"max_iter": 100,
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"tol": 1e-4,
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"random_state": 42,
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"algorithm": "lloyd"
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},
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"estimator_methods": {
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"inference": "predict"
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}
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},
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"data": {
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"preprocessing_kwargs": { "normalize": "standard" }
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}
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},
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"datasets": {
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"linear regression datasets": {
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"data": [
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{
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"source": "make_classification",
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"source": "make_regression",
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"generation_kwargs": {
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"n_classes": 2,
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"n_samples": 10000,
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"n_features": 64,
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"n_informative": 32
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"n_samples": 500000,
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"n_features": 50,
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"n_informative": 10,
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"noise": 20.0,
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"random_state": 42
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}
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},
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{
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"source": "make_regression",
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"generation_kwargs": {
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"n_samples": 100000,
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"n_features": 2000,
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"n_informative": 10,
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"noise": 60.0,
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"random_state": 42
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}
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},
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{
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"dataset": "year_prediction_msd",
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"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
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},
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{
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"dataset": "hepmass",
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"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
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}
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]
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},
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"algorithms": [
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{
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"algorithm": {
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"estimator": "RandomForestClassifier",
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"estimator_params": { "n_estimators": 50 }
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"random forest datasets": {
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"data": [
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{
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"source": "make_regression",
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"generation_kwargs": {
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"n_samples": 100000,
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"n_features": 20,
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"n_informative": 10,
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"noise": 10.0,
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"random_state": 42
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}
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},
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{
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"source": "make_regression",
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"generation_kwargs": {
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"n_samples": 50000,
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"n_features": 200,
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"n_informative": 20,
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"noise": 30.0,
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"random_state": 42
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}
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},
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{
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"dataset": "year_prediction_msd",
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"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
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},
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{
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"dataset": "medical_charges_nominal",
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"split_kwargs": { "ignore": true }
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}
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},
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{
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"algorithm": {
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"estimator": "KMeans",
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"estimator_params": {
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"n_clusters": 10,
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"init": "random",
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"algorithm": "lloyd",
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"max_iter": 100
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]
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},
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"knn datasets": {
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"data": [
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{
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"source": "make_classification",
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"generation_kwargs": {
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"n_classes": 5,
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"n_samples": 200000,
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"n_features": 10,
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"n_informative": 8,
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"n_redundant": 2,
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"n_repeated": 0,
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"random_state": 42
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}
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},
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{
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"source": "make_classification",
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"generation_kwargs": {
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"n_classes": 5,
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"n_samples": 50000,
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"n_features": 50,
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"n_informative": 20,
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"n_redundant": 10,
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"n_repeated": 0,
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"random_state": 42
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}
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},
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{
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"dataset": "letters",
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"split_kwargs": { "ignore": true }
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},
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{
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"dataset": "codrnanorm",
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"split_kwargs": { "ignore": true }
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}
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},
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{
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"algorithm": {
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"estimator": "LinearRegression"
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]
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},
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"kmeans datasets": {
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"data": [
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{
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"source": "make_blobs",
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"generation_kwargs": {
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"centers": 10,
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"cluster_std": 4.0,
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"n_samples": 500000,
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"n_features": 20,
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"random_state": 42
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}
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},
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{
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"source": "make_blobs",
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"generation_kwargs": {
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"centers": 10,
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"cluster_std": 8.0,
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"n_samples": 100000,
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"n_features": 200,
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"random_state": 42
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}
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},
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{
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"dataset": "creditcard",
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"split_kwargs": { "ignore": true }
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},
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{
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"dataset": "hepmass",
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"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
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}
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}
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]
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]
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}
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},
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"TEMPLATES": {
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"throughput_test": {
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"linear_regression_throughput": {
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"SETS": [
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"sklearn-ex[cpu] implementations",
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"throughput settings",
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"linear regression",
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"linear regression datasets"
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]
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},
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"random_forest_throughput": {
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"SETS": [
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"sklearn-ex[cpu] implementations",
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"throughput settings",
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"random forest regressor",
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"random forest datasets"
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]
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},
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"knn_throughput": {
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"SETS": [
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"sklearn-ex[cpu] implementations",
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"throughput settings",
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"knn classifier kdtree",
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"knn datasets"
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]
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},
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"kmeans_throughput": {
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"SETS": [
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"sklearn-ex[cpu] implementations",
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"common parameters",
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"throughput settings",
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"datasets",
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"algorithms"
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"kmeans",
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"kmeans datasets"
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]
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}
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}

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