geochemistrypi.data_mining package¶
Subpackages¶
- geochemistrypi.data_mining.data package
- Submodules
- geochemistrypi.data_mining.data.data_readiness module
- geochemistrypi.data_mining.data.feature_engineering module
- geochemistrypi.data_mining.data.imputation module
- geochemistrypi.data_mining.data.inference module
- geochemistrypi.data_mining.data.preprocessing module
- geochemistrypi.data_mining.data.statistic module
- Module contents
- geochemistrypi.data_mining.model package
- Subpackages
- Submodules
- geochemistrypi.data_mining.model.classification module
AdaBoostClassificationClassificationWorkflowBaseClassificationWorkflowBase.auto_modelClassificationWorkflowBase.common_componentsClassificationWorkflowBase.common_functionClassificationWorkflowBase.customizationClassificationWorkflowBase.customize_label()ClassificationWorkflowBase.fitClassificationWorkflowBase.manual_hyper_parameters()ClassificationWorkflowBase.predictClassificationWorkflowBase.sample_balance()ClassificationWorkflowBase.settings
DecisionTreeClassificationExtraTreesClassificationGradientBoostingClassificationKNNClassificationLogisticRegressionClassificationMLPClassificationRandomForestClassificationSGDClassificationSVMClassificationXGBoostClassification
- geochemistrypi.data_mining.model.clustering module
- geochemistrypi.data_mining.model.decomposition module
- geochemistrypi.data_mining.model.detection module
- geochemistrypi.data_mining.model.regression module
BayesianRidgeRegressionClassicalLinearRegressionDecisionTreeRegressionElasticNetRegressionExtraTreesRegressionGradientBoostingRegressionKNNRegressionLassoRegressionMLPRegressionPolynomialRegressionRandomForestRegressionRegressionWorkflowBaseRegressionWorkflowBase.auto_modelRegressionWorkflowBase.common_componentsRegressionWorkflowBase.common_functionRegressionWorkflowBase.customizationRegressionWorkflowBase.fitRegressionWorkflowBase.manual_hyper_parameters()RegressionWorkflowBase.predictRegressionWorkflowBase.ray_tune()RegressionWorkflowBase.settings
RidgeRegressionSGDRegressionSVMRegressionXGBoostRegression
- Module contents
- geochemistrypi.data_mining.plot package
- geochemistrypi.data_mining.process package
- geochemistrypi.data_mining.tests package
- geochemistrypi.data_mining.utils package
Submodules¶
geochemistrypi.data_mining.cli_pipeline module¶
- cli_pipeline(training_data_path: str, application_data_path: str | None = None, data_source: DataSource | None = None) None[source]¶
The command line interface software for Geochemistry π. The business logic of this CLI software can be found in the figures in the README.md file. It provides three MLOps core functionalities:
Continuous Training
Machine Learning Lifecycle Management
Model Inference
- Parameters:
training_data_path (str) – The path of the training data.
application_data_path (str, optional) – The path of the application data, by default None
geochemistrypi.data_mining.constants module¶
geochemistrypi.data_mining.dash_pipeline module¶
geochemistrypi.data_mining.enum module¶
- class DataSource(value)[source]¶
Bases:
EnumAn enumeration.
- ANY_PATH = 'Any Path'¶
- BUILT_IN = 'Built-in'¶
- DESKTOP = 'Desktop'¶