DashAI.back.models.LogisticRegression
- class LogisticRegression(**kwargs)[source]
Scikit-learn’s Logistic Regression wrapper for DashAI.
Methods
__init__(**kwargs)decision_function(X)Predict confidence scores for samples.
densify()Convert coefficient matrix to dense array format.
fit(x_train, y_train)Fit the estimator.
get_metadata_routing()Get metadata routing of this object.
get_params([deep])Get parameters for this estimator.
get_schema()Generates the component related Json Schema.
load(filename)Load the model of the specified path.
predict(x_pred)Make a prediction with the model.
predict_log_proba(X)Predict logarithm of probability estimates.
predict_proba(X)Probability estimates.
save(filename)Save the model in the specified path.
score(X, y[, sample_weight])Return the mean accuracy on the given test data and labels.
set_fit_request(*[, x_train, y_train])Request metadata passed to the
fitmethod.set_params(**params)Set the parameters of this estimator.
set_predict_request(*[, x_pred])Request metadata passed to the
predictmethod.set_score_request(*[, sample_weight])Request metadata passed to the
scoremethod.sparsify()Convert coefficient matrix to sparse format.
validate_and_transform(raw_data)It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Attributes
COMPATIBLE_COMPONENTSTYPE