sklearn.metrics Module: Difference between revisions
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An [[sklearn.metrics Module]] is an [[sklearn]] [[Python module|module]] that contains a collection of [[Metric]]s [[subroutine]]s. | An [[sklearn.metrics Module]] is an [[sklearn]] [[Python module|module]] that contains a collection of [[Metric]]s [[subroutine]]s. | ||
* <B>Context:</B> | * <B>Context:</B> | ||
** It can (often) reference a [[sklearn.metrics]] system. | ** It can (often) reference a [[sklearn.metrics Module|sklearn.metrics]] system. | ||
*** <code>[[sklearn.metrics]].<span style="font-weight:italic; color:green">Metric_Name(self, arguments)</i></code> or simply <code>[[sklearn.metrics]].<span style="font-weight:italic; color:green">Metric_Name()</i></code> <P>where <i>Metric_Name</i> is the name of the selected [[Metric]] [[subroutine]]. | *** <code>[[sklearn.metrics Module|sklearn.metrics]].<span style="font-weight:italic; color:green">Metric_Name(self, arguments)</i></code> or simply <code>[[sklearn.metrics Module|sklearn.metrics]].<span style="font-weight:italic; color:green">Metric_Name()</i></code> <P>where <i>Metric_Name</i> is the name of the selected [[Metric]] [[subroutine]]. | ||
** It can range from being [[Classification Metric]]s, to being [[Regression Metric]]s, to being [[Multilabel Ranking Metric]]s, to being [[Clustering Metric]]s, to being [[Biclustering Metric]]s, to being [[Pairwise Metric]]s. | ** It can range from being [[Classification Metric]]s, to being [[Regression Metric]]s, to being [[Multilabel Ranking Metric]]s, to being [[Clustering Metric]]s, to being [[Biclustering Metric]]s, to being [[Pairwise Metric]]s. | ||
* <B>Example(s)</B> | * <B>Example(s)</B> |
Revision as of 20:45, 23 December 2019
An sklearn.metrics Module is an sklearn module that contains a collection of Metrics subroutines.
- Context:
- It can (often) reference a sklearn.metrics system.
sklearn.metrics.Metric_Name(self, arguments)
or simplysklearn.metrics.Metric_Name()
where Metric_Name is the name of the selected Metric subroutine.
- It can range from being Classification Metrics, to being Regression Metrics, to being Multilabel Ranking Metrics, to being Clustering Metrics, to being Biclustering Metrics, to being Pairwise Metrics.
- It can (often) reference a sklearn.metrics system.
- Example(s)
- Counter-Example(s):
sklearn.manifold
, a collection of Manifold Learning Systems.sklearn.tree
, a collection of Decision Tree Learning Systems.sklearn.ensemble
, a collection of Decision Tree Ensemble Learning Systems.sklearn.covariance
,a collection of Covariance Estimators.sklearn.cluster.bicluster
, a collection of Spectral Biclustering Algorithms.sklearn.linear_model
, a collection of Linear Model Regression Systems.sklearn.neighbors
, a collection of K Nearest Neighbors Algorithms.sklearn.neural_network
, a collection of Neural Network Systems.
- See: Metric, Pairwise Distance, Clustering, Regression Analysis Task, Classification Task, MSE, RMSE.
References
2017A
- (Scikit Learn, 2017) ⇒ http://scikit-learn.org/stable/modules/classes.html#module-sklearn.metrics Retrieved:2017-11-12
- QUOTE: See the Model evaluation: quantifying the quality of predictions section and the Pairwise metrics, Affinities and Kernels section of the user guide for further details.
The sklearn.metrics module includes score functions, performance metrics and pairwise metrics and distance computations.
- QUOTE: See the Model evaluation: quantifying the quality of predictions section and the Pairwise metrics, Affinities and Kernels section of the user guide for further details.