colda.algorithm.model package

Submodules

colda.algorithm.model.api module

class colda.algorithm.model.api.Model(task_mode: Literal['classification', 'regression'], model_name: Literal['linear', 'decision_tree', 'svm', 'gradient_boosting', 'mlp'])

Bases: BaseModel

fit(data, target) → None

make_model(task_mode: Literal['classification', 'regression'], model_name: Literal['linear', 'decision_tree', 'svm', 'gradient_boosting', 'mlp']) → object

predict(data, target=None) → None

colda.algorithm.model.base module

class colda.algorithm.model.base.BaseModel

Bases: object

Base class for Model

final placeholder()

colda.algorithm.model.models module

class colda.algorithm.model.models.Model(task_mode: Literal['classification', 'regression'], model_name: Literal['linear', 'decision_tree', 'svm', 'gradient_boosting', 'mlp'])

Bases: BaseModel

fit(data, target) → None

make_model(task_mode: Literal['classification', 'regression'], model_name: Literal['linear', 'decision_tree', 'svm', 'gradient_boosting', 'mlp']) → object

predict(data, target=None) → None

colda.algorithm.model.models_prev module

class colda.algorithm.model.models_prev.Model(task_mode, model_name, model=None)

Bases: BaseModel

fit(data, target) → None

make_model(task_mode: Literal['classification', 'regression'], model_name: Literal['linear', 'decision_tree', 'svm', 'gradient_boosting', 'mlp']) → object

predict(data) → None

colda.algorithm.model.my_model module

class colda.algorithm.model.my_model.LSTMModel(num_sensors, hidden_units)

Bases: Module

fit(train_loader, epochs=10, lr=0.1)

forward(x)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

lstm_predict(test_dataloader)

training: bool

class colda.algorithm.model.my_model.SequenceDataset(sequence_length, dataframe_x, dataframe_y=None)

Bases: Dataset

colda.algorithm.model.my_model.SequenceDataset_handeler(dataset, target_dataset=None)

Module contents