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# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Modal for training.... | ```python
import os
os.environ.setdefault("MPLCONFIGDIR", "/tmp/mpl") # matplotlib cache on ephemeral fs
os.environ.setdefault("XLA_PYTHON_CLIENT_ALLOCATOR", "platform") # reduce OOM
import datasets
import modal
import numpy as np
import pandas as pd
import sklearn.metrics
from sklearn.base import BaseEstimator
from... | 145,966 | precision | precision_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
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6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
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f... | 2,575 | performance_145966_evalFOO_VLLM_task0_seed0.txt | <|im_start|>user
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Mo... |
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Modal for training.... | ```python
import os
os.environ.setdefault("MPLCONFIGDIR", "/tmp/mpl") # matplotlib cache on ephemeral fs
os.environ.setdefault("XLA_PYTHON_CLIENT_ALLOCATOR", "platform") # reduce OOM
import datasets
import modal
import numpy as np
import pandas as pd
import sklearn.metrics
from sklearn.base import BaseEstimator
from... | 145,966 | precision | precision_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
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f... | 2,575 | performance_145966_evalFOO_VLLM_task0_seed1.txt | <|im_start|>user
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Mo... |
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Modal for training.... | ```python
import os
os.environ.setdefault("MPLCONFIGDIR", "/tmp/mpl") # matplotlib cache on ephemeral fs
os.environ.setdefault("XLA_PYTHON_CLIENT_ALLOCATOR", "platform") # reduce OOM
import datasets
import modal
import numpy as np
import pandas as pd
import sklearn.metrics
from sklearn.base import BaseEstimator
from... | 145,966 | precision | precision_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
"att1",
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f... | 2,575 | performance_145966_evalFOO_VLLM_task0_seed2.txt | <|im_start|>user
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Mo... |
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Modal for training.... | ```python
import os
os.environ.setdefault("MPLCONFIGDIR", "/tmp/mpl") # matplotlib cache on ephemeral fs
os.environ.setdefault("XLA_PYTHON_CLIENT_ALLOCATOR", "platform") # reduce OOM
import datasets
import modal
import numpy as np
import pandas as pd
import sklearn.metrics
from sklearn.base import BaseEstimator
from... | 145,966 | precision | precision_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
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f... | 2,575 | performance_145966_evalFOO_VLLM_task0_seed3.txt | <|im_start|>user
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Mo... |
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Modal for training.... | ```python
import os
os.environ.setdefault("MPLCONFIGDIR", "/tmp/mpl") # matplotlib cache on ephemeral fs
os.environ.setdefault("XLA_PYTHON_CLIENT_ALLOCATOR", "platform") # reduce OOM
import datasets
import modal
import numpy as np
import sklearn.metrics
import pandas as pd
from sklearn.base import BaseEstimator
from... | 145,966 | precision | precision_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
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f... | 2,575 | performance_145966_evalFOO_VLLM_task0_seed4.txt | <|im_start|>user
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Mo... |
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Modal for training.... | ```python
import os
os.environ.setdefault("MPLCONFIGDIR", "/tmp/mpl") # matplotlib cache on ephemeral fs
os.environ.setdefault("XLA_PYTHON_CLIENT_ALLOCATOR", "platform") # reduce OOM
import datasets
import modal
import numpy as np
import pandas as pd
import sklearn.metrics
from sklearn.base import BaseEstimator
from... | 145,966 | precision | precision_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
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f... | 2,575 | performance_145966_evalFOO_VLLM_task0_seed5.txt | <|im_start|>user
# Role
You are an ML Engineer tasked with delivering an optimal solution for a regression or classification problem. You will receive a dataset and are expected to develop code that achieves the best possible performance using a specified scikit-learn metric. You have access to a single A10G GPU via Mo... |
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"# Role\nYou are an ML Engineer tasked with delivering an optimal solution for a regression or class(...TRUNCATED) | "```python\nimport os\nos.environ.setdefault(\"MPLCONFIGDIR\", \"/tmp/mpl\") # matplotlib cache on (...TRUNCATED) | 145,966 | precision | precision_score | mfeat-zernike | "**Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology \n**So(...TRUNCATED) | "{0: [0 - att1 (numeric)],\n 1: [1 - att2 (numeric)],\n 2: [2 - att3 (numeric)],\n 3: [3 - att4 (num(...TRUNCATED) | "{'MajorityClassSize': 200.0,\n 'MaxNominalAttDistinctValues': 10.0,\n 'MinorityClassSize': 200.0,\n(...TRUNCATED) | mfeat-zernike | ["att1","att2","att3","att4","att5","att6","att7","att8","att9","att10","att11","att12","att13","att(...TRUNCATED) | [false,false,false,false,false,false,false,false,false,false,false,false,false,false,false,false,fal(...TRUNCATED) | 2,575 | performance_145966_evalFOO_VLLM_task0_seed9.txt | "<|im_start|>user\n# Role\nYou are an ML Engineer tasked with delivering an optimal solution for a r(...TRUNCATED) |
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