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A collection of regression datasets

Project description

RegData

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A collection of regression datasets.

Install

pip install regdata

Quick example

import regdata as rd
rd.set_backend('torch') # numpy, tf (numpy is default)
X, y, X_test = rd.Step().get_data() # Loads step function dataset

Features

  • Simple API for quick benchmarking on various datasets.
  • Get data in any framework: torch, tensorflow or numpy by setting a global backend.
  • Scale X and/or y data with MinMaxScaler or StandardScaler.
  • Get y in squeezed (n,) or unsqueezed (n,1) format.
  • Perform only mean normalization on y.
  • Add custom noise to the observations (y).
  • Get consistent data with fixed random seed.

Plot datasets to have a quick glance

import regdata as rd
rd.Olympic().plot()

Checkout all plots here.

Datasets

from regdata import (
    DellaGattaGene,
    Heinonen4,
    Jump1D,
    MotorcycleHelmet,
    NonStat2D,
    Olympic,
    SineJump1D,
    SineNoisy,
    Smooth1D,
    Step
)

References

Project details


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Source Distribution

regdata-1.0.4.tar.gz (431.7 kB view hashes)

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