glmnet CV¶
-
class
glmnet_cv_regression.
csvCV
[source]¶ Functor that handles cross-validated glmnet regression for data supplied as a raw .csv ( Comma Seperated Value ) file.
-
__call__
(file_contents, regression_var)[source]¶ Run the regression and return the results.
- Args:
- file_contents: The raw contents of an HTTP POST request where form-data corresponds to a .csv file containing the design matrix, vector of predictors and any headers. regression_var: Index of the column that contains the vector of predictors.
- Returns:
- A pandas.DataFrame containing the regression coefficients corresponding to the support ( that is non-zero and signigiant coefficients ) along with the intercept term.
-
-
class
glmnet_cv_regression.
jsonCV
[source]¶ Functor that handles cross-validated glmnet regression for data supplied as a JSON string.
-
__call__
(json_blob, regression_var)[source]¶ Run the regression and return the results.
- Args:
- file_contents: The raw contents of an HTTP POST request where form-data corresponds to a JSON string containing the design matrix, vector of predictors and any headers. regression_var: Index of the column that contains the vector of predictors.
- Returns:
- A pandas.DataFrame containing the regression coefficients corresponding to the support ( that is non-zero and signigiant coefficients ) along with the intercept term.
-
-
class
glmnet_cv_regression.
multiCV
[source]¶ Base class that handles some of data preparation for regressions performed via cross-validated glmnet.
This class is not responsible for processing raw POST request form-data. It is assumed that the data has already been converted into a pandas DataFrame.
-
__weakref__
¶ list of weak references to the object (if defined)
-
-
class
glmnet_cv_regression.
xlsxCV
[source]¶ Functor that handles cross-validated glmnet regression for data supplied as a raw .xlsx ( Excel ) file.
-
__call__
(file_contents, regression_var)[source]¶ Run the regression and return the results.
- Args:
- file_contents: The raw contents of an HTTP POST request where form-data corresponds to a .xlsx file containing the design matrix, vector of predictors and any headers. regression_var: Index of the column that contains the vector of predictors.
- Returns:
- A pandas.DataFrame containing the regression coefficients corresponding to the support ( that is non-zero and signigiant coefficients ) along with the intercept term.
-