Docstring:
Usage: qiime sample-classifier classify-samples-from-dist [OPTIONS]
Run k-nearest-neighbors on a labeled distance matrix. Return cross-validated
(leave one out) predictions and accuracy. k = 1 by default
Inputs:
--i-distance-matrix ARTIFACT
DistanceMatrix a distance matrix [required]
Parameters:
--m-metadata-file METADATA
--m-metadata-column COLUMN MetadataColumn[Categorical]
Categorical metadata column to use as prediction
target. [required]
--p-k INTEGER Number of nearest neighbors [default: 1]
--p-cv INTEGER Number of k-fold cross-validations to perform.
Range(1, None) [default: 5]
--p-random-state INTEGER
Seed used by random number generator. [optional]
--p-n-jobs INTEGER Number of jobs to run in parallel. [default: 1]
--p-palette TEXT Choices('YellowOrangeBrown', 'YellowOrangeRed',
'OrangeRed', 'PurpleRed', 'RedPurple', 'BluePurple', 'GreenBlue',
'PurpleBlue', 'YellowGreen', 'summer', 'copper', 'viridis', 'cividis',
'plasma', 'inferno', 'magma', 'sirocco', 'drifting', 'melancholy',
'enigma', 'eros', 'spectre', 'ambition', 'mysteriousstains', 'daydream',
'solano', 'navarro', 'dandelions', 'deepblue', 'verve', 'greyscale')
The color palette to use for plotting.
[default: 'sirocco']
Outputs:
--o-predictions ARTIFACT SampleData[ClassifierPredictions]
leave one out predictions for each sample [required]
--o-accuracy-results VISUALIZATION
Accuracy results visualization. [required]
Miscellaneous:
--output-dir PATH Output unspecified results to a directory
--verbose / --quiet Display verbose output to stdout and/or stderr during
execution of this action. Or silence output if
execution is successful (silence is golden).
--example-data PATH Write example data and exit.
--citations Show citations and exit.
--help Show this message and exit.
Import:
from qiime2.plugins.sample_classifier.pipelines import classify_samples_from_dist
Docstring:
Run k-nearest-neighbors on a labeled distance matrix.
Run k-nearest-neighbors on a labeled distance matrix. Return cross-
validated (leave one out) predictions and accuracy. k = 1 by default
Parameters
----------
distance_matrix : DistanceMatrix
a distance matrix
metadata : MetadataColumn[Categorical]
Categorical metadata column to use as prediction target.
k : Int, optional
Number of nearest neighbors
cv : Int % Range(1, None), optional
Number of k-fold cross-validations to perform.
random_state : Int, optional
Seed used by random number generator.
n_jobs : Int, optional
Number of jobs to run in parallel.
palette : Str % Choices('YellowOrangeBrown', 'YellowOrangeRed', 'OrangeRed', 'PurpleRed', 'RedPurple', 'BluePurple', 'GreenBlue', 'PurpleBlue', 'YellowGreen', 'summer', 'copper', 'viridis', 'cividis', 'plasma', 'inferno', 'magma', 'sirocco', 'drifting', 'melancholy', 'enigma', 'eros', 'spectre', 'ambition', 'mysteriousstains', 'daydream', 'solano', 'navarro', 'dandelions', 'deepblue', 'verve', 'greyscale'), optional
The color palette to use for plotting.
Returns
-------
predictions : SampleData[ClassifierPredictions]
leave one out predictions for each sample
accuracy_results : Visualization
Accuracy results visualization.
