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1. add role level timeout 限制是1000s

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2. 修改log的层级逻辑
3. data.yaml 只用于存路径
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Yizhou Chi 2024-10-10 16:30:07 +08:00
parent 573e9b6d9e
commit f80ebc4d67
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expo/data.yaml
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@ -1,160 +1,3 @@
datasets_dir: "D:/work/automl/datasets" # path to the datasets directory
datasets:
titanic:
dataset: 04_titanic
metric: f1
target_col: Survived
user_requirement: "This is a 04_titanic dataset. Your goal is to predict the target\
\ column `Survived`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
\ or make any visualizations.\n"
house-prices:
dataset: 05_house-prices-advanced-regression-techniques
metric: rmse
target_col: SalePrice
user_requirement: "This is a 05_house-prices-advanced-regression-techniques dataset.\
\ Your goal is to predict the target column `SalePrice`.\nPerform data analysis,\
\ data preprocessing, feature engineering, and modeling to predict the target.\
\ \nReport rmse on the eval data. Do not plot or make any visualizations.\n"
santander-customer:
dataset: 06_santander-customer-transaction-prediction
metric: f1
target_col: target
user_requirement: "This is a 06_santander-customer-transaction-prediction dataset.\
\ Your goal is to predict the target column `target`.\nPerform data analysis,\
\ data preprocessing, feature engineering, and modeling to predict the target.\
\ \nReport f1 on the eval data. Do not plot or make any visualizations.\n"
icr:
dataset: 07_icr-identify-age-related-conditions
metric: f1
target_col: Class
user_requirement: "This is a 07_icr-identify-age-related-conditions dataset. Your\
\ goal is to predict the target column `Class`.\nPerform data analysis, data\
\ preprocessing, feature engineering, and modeling to predict the target. \n\
Report f1 on the eval data. Do not plot or make any visualizations.\n"
Click_prediction_small:
dataset: Click_prediction_small
metric: f1
target_col: click
user_requirement: "This is a Click_prediction_small dataset. Your goal is to predict\
\ the target column `click`.\nPerform data analysis, data preprocessing, feature\
\ engineering, and modeling to predict the target. \nReport f1 on the eval data.\
\ Do not plot or make any visualizations.\n"
GesturePhaseSegmentationProcessed:
dataset: GesturePhaseSegmentationProcessed
metric: f1 weighted
target_col: Phase
user_requirement: "This is a GesturePhaseSegmentationProcessed dataset. Your goal\
\ is to predict the target column `Phase`.\nPerform data analysis, data preprocessing,\
\ feature engineering, and modeling to predict the target. \nReport f1 weighted\
\ on the eval data. Do not plot or make any visualizations.\n"
Moneyball:
dataset: Moneyball
metric: rmse
target_col: RS
user_requirement: "This is a Moneyball dataset. Your goal is to predict the target\
\ column `RS`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport rmse on the eval data. Do not\
\ plot or make any visualizations.\n"
SAT11-HAND-runtime-regression:
dataset: SAT11-HAND-runtime-regression
metric: rmse
target_col: runtime
user_requirement: "This is a SAT11-HAND-runtime-regression dataset. Your goal\
\ is to predict the target column `runtime`.\nPerform data analysis, data preprocessing,\
\ feature engineering, and modeling to predict the target. \nReport rmse on\
\ the eval data. Do not plot or make any visualizations.\n"
boston:
dataset: boston
metric: rmse
target_col: MEDV
user_requirement: "This is a boston dataset. Your goal is to predict the target\
\ column `MEDV`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport rmse on the eval data. Do not\
\ plot or make any visualizations.\n"
colleges:
dataset: colleges
metric: rmse
target_col: percent_pell_grant
user_requirement: "This is a colleges dataset. Your goal is to predict the target\
\ column `percent_pell_grant`.\nPerform data analysis, data preprocessing, feature\
\ engineering, and modeling to predict the target. \nReport rmse on the eval\
\ data. Do not plot or make any visualizations.\n"
credit-g:
dataset: credit-g
metric: f1
target_col: class
user_requirement: "This is a credit-g dataset. Your goal is to predict the target\
\ column `class`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
\ or make any visualizations.\n"
diamonds:
dataset: diamonds
metric: rmse
target_col: price
user_requirement: "This is a diamonds dataset. Your goal is to predict the target\
\ column `price`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport rmse on the eval data. Do not\
\ plot or make any visualizations.\n"
jasmine:
dataset: jasmine
metric: f1
target_col: class
user_requirement: "This is a jasmine dataset. Your goal is to predict the target\
\ column `class`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
\ or make any visualizations.\n"
kc1:
dataset: kc1
metric: f1
target_col: defects
user_requirement: "This is a kc1 dataset. Your goal is to predict the target column\
\ `defects`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
\ or make any visualizations.\n"
kick:
dataset: kick
metric: f1
target_col: IsBadBuy
user_requirement: "This is a kick dataset. Your goal is to predict the target\
\ column `IsBadBuy`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport f1 on the eval data. Do not plot\
\ or make any visualizations.\n"
mfeat-factors:
dataset: mfeat-factors
metric: f1 weighted
target_col: class
user_requirement: "This is a mfeat-factors dataset. Your goal is to predict the\
\ target column `class`.\nPerform data analysis, data preprocessing, feature\
\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
\ eval data. Do not plot or make any visualizations.\n"
segment:
dataset: segment
metric: f1 weighted
target_col: class
user_requirement: "This is a segment dataset. Your goal is to predict the target\
\ column `class`.\nPerform data analysis, data preprocessing, feature engineering,\
\ and modeling to predict the target. \nReport f1 weighted on the eval data.\
\ Do not plot or make any visualizations.\n"
steel-plates-fault:
dataset: steel-plates-fault
metric: f1 weighted
target_col: target
user_requirement: "This is a steel-plates-fault dataset. Your goal is to predict\
\ the target column `target`.\nPerform data analysis, data preprocessing, feature\
\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
\ eval data. Do not plot or make any visualizations.\n"
wine-quality-white:
dataset: wine-quality-white
metric: f1 weighted
target_col: Class
user_requirement: "This is a wine-quality-white dataset. Your goal is to predict\
\ the target column `Class`.\nPerform data analysis, data preprocessing, feature\
\ engineering, and modeling to predict the target. \nReport f1 weighted on the\
\ eval data. Do not plot or make any visualizations.\n"
work_dir: ../workspace # path to the workspace directory
role_dir: storage/team/environment/roles/ResearchAssistant_David
# analysis_pool_dir: D:/work/MG-open/MetaGPT/examples/MCTS_test/analysis_pool_sample.json
role_dir: storage/SELA # path to the role directory