isanet.utils¶

isanet.utils.model_utils.load_data(filename)¶

Deserialize and load an object from a specific path.

Parameters: filename (string) – Specifies the name of the file to load to.
Returns: the deserialized object returns
Return type: objct

isanet.utils.model_utils.plotHistory(history, loss='MSE', orientation='horizontal')¶

Plots the learning curve for the training and the validation for for a specific loss and accuracy.

Parameters

history (dict) – It contains for each epoch the values of mse, mee and accuracy for training and validation and the time.
loss (string, accepted value == ("MSE", "MEE")) – Specifies what type of loss to use.
orientation (None, "horizontal", "vertical") – Indicates the orientation of the two plots.

isanet.utils.model_utils.plotMse(history)¶

Plots the learning curve for the training and the validation for for MSE.

Parameters: history (dict) – It contains for each epoch the values of mse, mee and accuracy for training and validation and the time.

isanet.utils.model_utils.printAcc(y_pred, y_true, type='')¶

Print to the stout the MSE value.

Parameters

y_true (array-like of shape (n_samples,) or (n_samples, n_outputs)) – Ground truth (correct) target values.
y_pred (array-like of shape (n_samples,) or (n_samples, n_outputs)) – Estimated target values.
type (string) – Useful to specify what kind of mse you are going to print. E.g. Train, Test or Val.

isanet.utils.model_utils.printMEE(y_pred, y_true, type='')¶

Print to the stout the MEE value.

Parameters

y_true (array-like of shape (n_samples,) or (n_samples, n_outputs)) – Ground truth (correct) target values.
y_pred (array-like of shape (n_samples,) or (n_samples, n_outputs)) – Estimated target values.
type (string) – Useful to specify what kind of mse you are going to print. E.g. Train, Test or Val.

isanet.utils.model_utils.printMSE(y_pred, y_true, type='')¶

Print to the stout the MSE value.

Parameters

y_true (array-like of shape (n_samples,) or (n_samples, n_outputs)) – Ground truth (correct) target values.
y_pred (array-like of shape (n_samples,) or (n_samples, n_outputs)) – Estimated target values.
type (string) – Useful to specify what kind of mse you are going to print. E.g. Train, Test or Val.

isanet.utils.model_utils.save_data(data, filename)¶

Serialize and save the past object on file.

Parameters