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26 lines
1.1 KiB
Markdown
26 lines
1.1 KiB
Markdown
The function makes a labelled confusion matrix comparing predictions and ground truth labels.
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If classes is passed, confusion matrix will be labelled, if not, integer class values will be used.
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Args:
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* `y_true`: Array of truth labels (must be same shape as y_pred).
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* `y_pred`: Array of predicted labels (must be same shape as y_true).
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* `classes`: Array of class labels (e.g. string form). If `None`, integer labels are used.
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* `figsize`: Size of output figure (default=(10, 10)).
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* `text_size`: Size of output figure text (default=15).
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* `norm`: normalize values or not (default=False).
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* `savefig`: save confusion matrix to file (default=False).
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Returns: A labelled confusion matrix plot comparing y_true and y_pred.
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### Example usage:
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> """make_confusion_matrix(y_true=test_labels, # ground truth test labels
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y_pred=y_preds, # predicted labels
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classes=class_names, # array of class label names
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figsize=(15, 15),
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text_size=10)"""
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#### CODE BY ZeroToMastery TensorFlow course.
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