mirror of
https://github.com/FoundationAgents/MetaGPT.git
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225 lines
11 KiB
YAML
225 lines
11 KiB
YAML
datasets:
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titanic:
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dataset: 04_titanic
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metric: f1
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target_col: Survived
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user_requirement: "This is a 04_titanic dataset. Your goal is to predict the target\
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\ column `Survived`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
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\ or make any visualizations.\n"
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house-prices:
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dataset: 05_house-prices-advanced-regression-techniques
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metric: rmse
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target_col: SalePrice
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user_requirement: "This is a 05_house-prices-advanced-regression-techniques dataset.\
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\ Your goal is to predict the target column `SalePrice`.\nPerform data analysis,\
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\ data preprocessing, feature engineering, and modeling to predict the target.\
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\ \nReport rmse on the eval data. Do not plot or make any visualizations.\n"
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santander-customer:
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dataset: 06_santander-customer-transaction-prediction
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metric: f1
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target_col: target
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user_requirement: "This is a 06_santander-customer-transaction-prediction dataset.\
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\ Your goal is to predict the target column `target`.\nPerform data analysis,\
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\ data preprocessing, feature engineering, and modeling to predict the target.\
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\ \nReport f1 on the eval data. Do not plot or make any visualizations.\n"
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icr:
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dataset: 07_icr-identify-age-related-conditions
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metric: f1
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target_col: Class
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user_requirement: "This is a 07_icr-identify-age-related-conditions dataset. Your\
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\ goal is to predict the target column `Class`.\nPerform data analysis, data\
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\ preprocessing, feature engineering, and modeling to predict the target. \n\
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Report f1 on the eval data. Do not plot or make any visualizations.\n"
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Click_prediction_small:
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dataset: Click_prediction_small
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metric: f1
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target_col: click
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user_requirement: "This is a Click_prediction_small dataset. Your goal is to predict\
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\ the target column `click`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 on the eval data.\
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\ Do not plot or make any visualizations.\n"
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GesturePhaseSegmentationProcessed:
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dataset: GesturePhaseSegmentationProcessed
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metric: f1 weighted
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target_col: Phase
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user_requirement: "This is a GesturePhaseSegmentationProcessed dataset. Your goal\
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\ is to predict the target column `Phase`.\nPerform data analysis, data preprocessing,\
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\ feature engineering, and modeling to predict the target. \nReport f1 weighted\
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\ on the eval data. Do not plot or make any visualizations.\n"
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Moneyball:
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dataset: Moneyball
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metric: rmse
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target_col: RS
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user_requirement: "This is a Moneyball dataset. Your goal is to predict the target\
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\ column `RS`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport rmse on the eval data. Do not\
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\ plot or make any visualizations.\n"
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SAT11-HAND-runtime-regression:
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dataset: SAT11-HAND-runtime-regression
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metric: rmse
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target_col: runtime
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user_requirement: "This is a SAT11-HAND-runtime-regression dataset. Your goal\
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\ is to predict the target column `runtime`.\nPerform data analysis, data preprocessing,\
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\ feature engineering, and modeling to predict the target. \nReport rmse on\
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\ the eval data. Do not plot or make any visualizations.\n"
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boston:
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dataset: boston
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metric: rmse
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target_col: MEDV
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user_requirement: "This is a boston dataset. Your goal is to predict the target\
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\ column `MEDV`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport rmse on the eval data. Do not\
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\ plot or make any visualizations.\n"
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colleges:
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dataset: colleges
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metric: rmse
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target_col: percent_pell_grant
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user_requirement: "This is a colleges dataset. Your goal is to predict the target\
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\ column `percent_pell_grant`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport rmse on the eval\
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\ data. Do not plot or make any visualizations.\n"
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concrete-strength:
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dataset: concrete-strength
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metric: rmse
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target_col: Strength
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user_requirement: "This is a concrete-strength dataset. Your goal is to predict\
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\ the target column `Strength`.\nPerform data analysis, data preprocessing,\
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\ feature engineering, and modeling to predict the target. \nReport rmse on\
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\ the eval data. Do not plot or make any visualizations.\n"
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credit-g:
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dataset: credit-g
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metric: f1
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target_col: class
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user_requirement: "This is a credit-g dataset. Your goal is to predict the target\
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\ column `class`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
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\ or make any visualizations.\n"
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diamonds:
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dataset: diamonds
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metric: rmse
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target_col: price
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user_requirement: "This is a diamonds dataset. Your goal is to predict the target\
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\ column `price`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport rmse on the eval data. Do not\
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\ plot or make any visualizations.\n"
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jasmine:
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dataset: jasmine
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metric: f1
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target_col: class
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user_requirement: "This is a jasmine dataset. Your goal is to predict the target\
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\ column `class`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
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\ or make any visualizations.\n"
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kc1:
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dataset: kc1
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metric: f1
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target_col: defects
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user_requirement: "This is a kc1 dataset. Your goal is to predict the target column\
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\ `defects`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
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\ or make any visualizations.\n"
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kick:
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dataset: kick
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metric: f1
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target_col: IsBadBuy
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user_requirement: "This is a kick dataset. Your goal is to predict the target\
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\ column `IsBadBuy`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
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\ or make any visualizations.\n"
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mfeat-factors:
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dataset: mfeat-factors
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metric: f1 weighted
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target_col: class
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user_requirement: "This is a mfeat-factors dataset. Your goal is to predict the\
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\ target column `class`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
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\ eval data. Do not plot or make any visualizations.\n"
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segment:
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dataset: segment
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metric: f1 weighted
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target_col: class
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user_requirement: "This is a segment dataset. Your goal is to predict the target\
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\ column `class`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 weighted on the eval data.\
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\ Do not plot or make any visualizations.\n"
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smoker-status:
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dataset: smoker-status
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metric: f1
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target_col: smoking
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user_requirement: "This is a smoker-status dataset. Your goal is to predict the\
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\ target column `smoking`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 on the eval data.\
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\ Do not plot or make any visualizations.\n"
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software-defects:
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dataset: software-defects
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metric: f1
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target_col: defects
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user_requirement: "This is a software-defects dataset. Your goal is to predict\
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\ the target column `defects`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 on the eval data.\
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\ Do not plot or make any visualizations.\n"
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steel-plates-fault:
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dataset: steel-plates-fault
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metric: f1 weighted
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target_col: target
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user_requirement: "This is a steel-plates-fault dataset. Your goal is to predict\
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\ the target column `target`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
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\ eval data. Do not plot or make any visualizations.\n"
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wine-quality-white:
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dataset: wine-quality-white
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metric: f1 weighted
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target_col: Class
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user_requirement: "This is a wine-quality-white dataset. Your goal is to predict\
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\ the target column `Class`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
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\ eval data. Do not plot or make any visualizations.\n"
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banking77:
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dataset: banking77
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metric: f1 weighted
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target_col: label
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user_requirement: "This is a banking77 dataset. Your goal is to predict the target\
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\ column `label`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 weighted on the eval data.\
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\ Do not plot or make any visualizations.\n"
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fashion_mnist:
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dataset: fashion_mnist
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metric: f1 weighted
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target_col: label
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user_requirement: "This is a fashion_mnist dataset. Your goal is to predict the\
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\ target column `label`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
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\ eval data. Do not plot or make any visualizations.\n"
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gnad10:
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dataset: gnad10
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metric: f1 weighted
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target_col: label
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user_requirement: "This is a gnad10 dataset. Your goal is to predict the target\
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\ column `label`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 weighted on the eval data.\
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\ Do not plot or make any visualizations.\n"
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oxford-iiit-pet:
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dataset: oxford-iiit-pet
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metric: f1 weighted
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target_col: label
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user_requirement: "This is a oxford-iiit-pet dataset. Your goal is to predict\
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\ the target column `label`.\nPerform data analysis, data preprocessing,\
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\ feature engineering, and modeling to predict the target. \nReport f1 weighted on the\
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\ eval data. Do not plot or make any visualizations.\n"
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sms_spam:
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dataset: sms_spam
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metric: f1
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target_col: label
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user_requirement: "This is a sms_spam dataset. Your goal is to predict the target\
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\ column `label`.\nPerform data analysis, data preprocessing, feature engineering,\
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\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
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\ or make any visualizations.\n"
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stanford_cars:
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dataset: stanford_cars
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metric: f1 weighted
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target_col: label
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user_requirement: "This is a stanford_cars dataset. Your goal is to predict the\
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\ target column `label`.\nPerform data analysis, data preprocessing, feature\
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\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
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\ eval data. Do not plot or make any visualizations.\n"
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