mean_squared_error¶
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pai4sk.sml_metrics.mean_squared_error(data, pred)¶ Distributed mean squared error regression loss. It supports both local and distributed(MPI) implementation.
This metric is often used in multi-class classification to compute the mean squared error of the predicted target values when compared with the true labels. It currently supports binary classification only. The metric is implemented in a distributed manner for MPI execution.
- Parameters
data (Supports the following input data-types :) –
Dense matrix (ndarray) of correct labels.
SnapML data partition. This includes the correct labels.
pred (Predicted target values.) – array-like, shape = (n_samples,)
- Returns
mean_squared_error_value – Returns the mean squared error of the predicted target values (pred) when compared with the true values (data).
- Return type