Docstring:
Usage: qiime sample-classifier confusion-matrix [OPTIONS]
Make a confusion matrix and calculate accuracy of predicted vs. true
values for a set of samples classified using a sample classifier.
Options:
--i-predictions ARTIFACT PATH SampleData[ClassifierPredictions]
Predicted values to plot on x axis. Should
be predictions of categorical data produced
by a sample classifier. [required]
--m-truth-file MULTIPLE FILE Metadata file or artifact viewable as
metadata. This option may be supplied
multiple times to merge metadata.
[required]
--m-truth-column MetadataColumn[Categorical]
Column from metadata file or artifact
viewable as metadata. Metadata column (true
values) to plot on y axis. [required]
--p-missing-samples [ignore|error]
How to handle missing samples in metadata.
"error" will fail if missing samples are
detected. "ignore" will cause the feature
table and metadata to be filtered, so that
only samples found in both files are
retained. [default: error]
--p-palette [BluePurple|PurpleBlue|drifting|melancholy|YellowOrangeBrown|viridis|solano|spectre|enigma|eros|daydream|deepblue|copper|summer|plasma|magma|mysteriousstains|inferno|dandelions|GreenBlue|YellowOrangeRed|sirocco|YellowGreen|PurpleRed|OrangeRed|verve|navarro|ambition|RedPurple|greyscale]
The color palette to use for plotting.
[default: sirocco]
--o-visualization VISUALIZATION PATH
[required if not passing --output-dir]
--output-dir DIRECTORY Output unspecified results to a directory
--cmd-config FILE Use config file for command options
--verbose Display verbose output to stdout and/or
stderr during execution of this action.
[default: False]
--quiet Silence output if execution is successful
(silence is golden). [default: False]
--citations Show citations and exit.
--help Show this message and exit.
Import:
from qiime2.plugins.sample_classifier.visualizers import confusion_matrix
Docstring:
Make a confusion matrix from sample classifier predictions.
Make a confusion matrix and calculate accuracy of predicted vs. true values
for a set of samples classified using a sample classifier.
Parameters
----------
predictions : SampleData[ClassifierPredictions]
Predicted values to plot on x axis. Should be predictions of
categorical data produced by a sample classifier.
truth : MetadataColumn[Categorical]
Metadata column (true values) to plot on y axis.
missing_samples : Str % Choices({'error', 'ignore'}), optional
How to handle missing samples in metadata. "error" will fail if missing
samples are detected. "ignore" will cause the feature table and
metadata to be filtered, so that only samples found in both files are
retained.
palette : Str % Choices({'BluePurple', 'GreenBlue', 'OrangeRed', 'PurpleBlue', 'PurpleRed', 'RedPurple', 'YellowGreen', 'YellowOrangeBrown', 'YellowOrangeRed', 'ambition', 'copper', 'dandelions', 'daydream', 'deepblue', 'drifting', 'enigma', 'eros', 'greyscale', 'inferno', 'magma', 'melancholy', 'mysteriousstains', 'navarro', 'plasma', 'sirocco', 'solano', 'spectre', 'summer', 'verve', 'viridis'}), optional
The color palette to use for plotting.
Returns
-------
visualization : Visualization
