Skip to main content

Creates the Precision-Recall-Gain curve and calculates the area under the curve

Project description

What are the Precision-Recall-Gain curves?

Please see http://www.cs.bris.ac.uk/~flach/PRGcurves/.

Contents

This package provides the following 6 functions:

precision_gain(TP,FN,FP,TN)
recall_gain(TP,FN,FP,TN)
create_prg_curve(labels,pos_scores)
calc_auprg(prg_curve)
prg_convex_hull(prg_curve)
plot_prg(prg_curve)

Installation

This package can be installed using pip from command line:

pip install pyprg

Usage

Detailed information about the usage can be seen in the manual pages of the individual functions, e.g. by typing ?prg.create_prg_curve after importing with from pyprg import prg. The example usage is as follows:

from pyprg import prg
import numpy as np
labels = np.array([1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,0,0,0,1,0,1], dtype='int')
scores = np.arange(1,26)[::-1]
prg_curve = prg.create_prg_curve(labels, scores, create_crossing_points=True)
auprg = prg.calc_auprg(prg_curve)
print(auprg)
prg.plot_prg(prg_curve)

Authors

This package has been written by Meelis Kull, Telmo de Menezes e Silva Filho, Miquel Perello Nieto, based on work by Peter Flach and Meelis Kull, see http://www.cs.bris.ac.uk/~flach/PRGcurves/.

Project details


Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page