azureml.train.automl.model_proxy azureml.train.automl.run azureml.train.automl.utilities azureml.train.automl.runtime azureml.train.dnn azureml.train.estimator azureml.train.hyperdrive azureml.train.sklearn azureml.training.tabular azureml.widgets ...
开发者ID:nok,项目名称:scikit-learn-model-porting,代码行数:12,代码来源:Ruby.py 示例3: main ▲点赞 3▼ # 需要导入模块: from sklearn_porter import Porter [as 别名]# 或者: from sklearn_porter.Porter importexport[as 别名]defmain():args = parse_args(sys.argv[1:])# Check input data:pkl...
tpot.export('%s%s_tpot_exported_pipeline.py'%(folder,type_) ) print('finished model selection')""" from sklearn.ensemble import VotingClassifier from sklearn.feature_selection import SelectFwe, f_classif from sklearn.model_selection import train_test_split from sklearn.neighbors import KNeighbo...
The main module ofNyokaisnyoka. To use it for your model, you need to import the specific exporter from nyoka as - Note - If scikit-learn, xgboost and lightgbm model is used then the model should be used inside sklearn's Pipeline. ...
model---siglip_model---README.md model---vision_utils.py.md web_server.py.md numpy-ml-ai numpy paddleocr-ai pandas-ta pandas pokellmon python-markdown-ai pytorch pyzelda-ai qlora-ai rwkv scipy sd-webui-ai seaborn segany-ai sensevoice simcse simupy sklearn so-...
react函数组件为了保持引用不变，很多时候需要借助useCallback，但是useCallback强依赖于外部变量，必须传个...
mlflow.sklearn.save_model(lr, modelpath) 針對MLlib 模型,請使用ML 管線。 下載模型成品。 你可以使用各種 API 下載已註冊模型的記錄模型成品(例如模型檔案、繪圖和計量)。 Python API範例: Python複製 frommlflow.store.artifact.models_artifact_repoimportModelsArtifactRepository ...
modelpath = "/dbfs/my_project_models/model-%f-%f" % (alpha, l1_ratio) mlflow.sklearn.save_model(lr, modelpath) 对于MLlib 模型,请使用 ML 管道。 下载模型项目 可以使用各种 API 下载已注册的模型的已记录模型项目(例如模型文件、绘图和指标)。 Python API 示例: Python 复制 from mlflow.store...
modelpath = "/dbfs/my_project_models/model-%f-%f" % (alpha, l1_ratio) mlflow.sklearn.save_model(lr, modelpath) 針對MLlib 模型,請使用 ML 管線。 下載模型成品 您可以使用各種 API 下載已註冊模型的記錄模型成品(例如模型檔案、繪圖和計量)。 Python API 範例: Python 複製 from mlflow.store.ar...
importpandasaspdimportnumpyasnpfromsklearnimporttreefromsklearnimportmetricsfromsklearn.model_selectionimporttrain_test_splitfromsklearn.datasetsimportload_irisiris=load_iris()clf=tree.DecisionTreeClassifier()feature_names=['sepal_length','sepal_width','petal_length','petal_width']data=pd.DataFrame(iris...