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title: Sklearn Proxy | |
tags: | |
- evaluate | |
- metric | |
description: "TODO: add a description here" | |
sdk: gradio | |
sdk_version: 3.0.2 | |
app_file: app.py | |
pinned: false | |
# Metric Card for Sklearn Proxy | |
***Module Card Instructions:*** *Fill out the following subsections. Feel free to take a look at existing metric cards if you'd like examples.* | |
## Metric Description | |
*Give a brief overview of this metric, including what task(s) it is usually used for, if any.* | |
## How to Use | |
*Give general statement of how to use the metric* | |
*Provide simplest possible example for using the metric* | |
### Inputs | |
*List all input arguments in the format below* | |
- **input_field** *(type): Definition of input, with explanation if necessary. State any default value(s).* | |
### Output Values | |
*Explain what this metric outputs and provide an example of what the metric output looks like. Modules should return a dictionary with one or multiple key-value pairs, e.g. {"bleu" : 6.02}* | |
*State the range of possible values that the metric's output can take, as well as what in that range is considered good. For example: "This metric can take on any value between 0 and 100, inclusive. Higher scores are better."* | |
#### Values from Popular Papers | |
*Give examples, preferrably with links to leaderboards or publications, to papers that have reported this metric, along with the values they have reported.* | |
### Examples | |
*Give code examples of the metric being used. Try to include examples that clear up any potential ambiguity left from the metric description above. If possible, provide a range of examples that show both typical and atypical results, as well as examples where a variety of input parameters are passed.* | |
## Limitations and Bias | |
*Note any known limitations or biases that the metric has, with links and references if possible.* | |
## Citation | |
*Cite the source where this metric was introduced.* | |
## Further References | |
*Add any useful further references.* | |