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classify-samples-from-dist: Run k-nearest-neighbors on a labeled distance matrix.¶
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 NTHREADS 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). --recycle-pool TEXT Use a cache pool for pipeline resumption. QIIME 2 will cache your results in this pool for reuse by future invocations. These pool are retained until deleted by the user. If not provided, QIIME 2 will create a pool which is automatically reused by invocations of the same action and removed if the action is successful. Note: these pools are local to the cache you are using. --no-recycle Do not recycle results from a previous failed pipeline run or save the results from this run for future recycling. --parallel Execute your action in parallel. This flag will use your default parallel config. --parallel-config FILE Execute your action in parallel using a config at the indicated path. --example-data PATH Write example data and exit. --citations Show citations and exit. --use-cache DIRECTORY Specify the cache to be used for the intermediate work of this action. If not provided, the default cache under $TMP/qiime2/will be used. IMPORTANT FOR HPC USERS: If you are on an HPC system and are using parallel execution it is important to set this to a location that is globally accessible to all nodes in the cluster. --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 : Threads, 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.