dlpy.metrics.confusion_matrix¶
-
dlpy.metrics.
confusion_matrix
(y_true, y_pred, castable=None, labels=None, id_vars=None)¶ Computes the confusion matrix of a classification task.
- Parameters
- y_truestring or
CASColumn
The column of the ground truth labels. If it is a string, then y_pred has to be a string and they both belongs to the same CASTable specified by the castable argument. If it is a
CASColumn
, then y_pred has to be aCASColumn
, and the castable argument is ignored. When both y_pred and y_true areCASColumn
, they can be in different CASTables.- y_predstring or
CASColumn
The column of the predicted class labels. If it is a string, then y_true has to be a string and they both belongs to the same CASTable specified by the castable argument. If it is a
CASColumn
, then y_true has to be aCASColumn
, and the castable argument is ignored. When both y_pred and y_true areCASColumn
, they can be in different CASTables.- castable
CASTable
, optional The CASTable object to use as the source if the y_pred and y_true are strings. Default = None
- labelslist, optional
List of labels that can be used to reorder the matrix or select the subset of the labels. If
labels=None
, all labels are included. Default=None- id_varsstring or list of strings, optional
Column names that serve as unique id for y_true and y_pred if they are from different CASTables. The column names need to appear in both CASTables, and they serve to match y_true and y_pred appropriately, since observation orders can be shuffled in distributed computing environment. Default = None
- y_truestring or
- Returns
pandas.DataFrame
The column index is the predicted class labels. The row index is the ground truth class labels.