scientistmetrics is a Python package for metrics and scoring : quantifying the quality of predictions

scientistmetrics provides the option for computing one of six measures of association between two nominal variables from the data given in a 2d contingency table:

• Chi - squard test : https://en.wikipedia.org/wiki/Chi-squared_test
• Cramer's V : https://en.wikipedia.org/wiki/Cram%C3%A9r%27s_V
• Tschuprow's T : https://en.wikipedia.org/wiki/Tschuprow%27s_T
• G-test : https://en.wikipedia.org/wiki/G-test
• Phi coefficient : https://en.wikipedia.org/wiki/Phi_coefficient
• Pearson contingence coefficient : https://www.statisticshowto.com/contingency-coefficient/

scientistmetrics provides metrics for classification problem :

• accuracy score
• f1 score
• precision
• recall
• etc...

scientistmetrics provides metrics for regression problem :

• Rsquared
• Adjusted Rsquared
• Mean squared error
• etc...

scientistmetrics provides a function that gives a set of all subsets model.

Notebook is availabled.

scientistmetrics requires :

python >=3.10
numpy >=1.26.4
pandas >=2.2.2
scikit-learn >=1.2.2
plotnine >=0.10.1
statsmodels >=0.14.0
scipy >=1.10.1

You can install scientistmetrics using pip :

pip install scientistmetrics

Duvérier DJIFACK ZEBAZE duverierdjifack@gmail.com