numetrics 0.2.1

Package For Numerai users to check their models performance

Numetrics

Numetrics is a small package that has some functions regarding checking the performance of a model's predictions.

Version

• Github Release v0.2.1
• PyPi Version v0.2.1

Why did I create Numetrics?

1. The first reason is: I want to contribute to the Numerai community. I have learned a lot from Arbitrage, JRB, Wigglemuse, Michael Oliver, the team, and everybody in the community.
2. The second reason is: I was tired of copying and pasting my code throughout my notebooks, so I decided to create a package to make it easier for me to just install it through pip

How to install Numetrics?

You can install it with pip

pip install numetrics

import numetrics

How to use Numetrics?

You have one function called diagnose this is the main function that does all the magic. It takes a dataframe of your prediction. Dataframe format should be same as the one you submit to Numerai. Prediction dataframe must have the following

• The id
• predicton column

you can just pass only the predicton dataframe

 numetrics.diagnose(example_prediction)

or you can spicify the target name and the predicton name

 numetrics.diagnose(preds_df,PREDICTION_NAME='prediction')

See the example file to learn how to use this package.

This is the first version/draft/attempt of the package. The code does not look pretty and it still missing lots of functionalities. However, I promise I will do my best to make it better ASAP.

Feel free to contribute to this package.

Change Log

0.0.1 (Nov/09/2020)

• First Release

0.0.2 (Nov/11/2020)

• Edited setup.py

0.0.3 (Nov/11/2020)

• Added Readme

0.0.4 (Nov/11/2020)

• Edited Readme

0.0.5 (Nov/13/2020)

• Added val data file
• Added beta_dignose function

0.1.0 (Nov/14/2020)

• Added data file and fixed the file path error
• Added beta_dignose function

0.2.0 (Nov/18/2020)

• Upgraded beta_dignose to diagnose and then deleted the old diagnose
• Changed data file
• Changed example prediction

0.2.1 (Nov/28/2020)

• Added the feature of calcualting diffrences between Vals