https://github.com/steviecurran/prediction-plot

Code to performs machine learning (k-nearest neighbours regression) and plot the predicted versus measured values
https://github.com/steviecurran/prediction-plot

astrophysics c data-analysis high-redshift machine-learning pgplot python statistics tensorflow visualization

Last synced: 7 months ago
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Code to performs machine learning (k-nearest neighbours regression) and plot the predicted versus measured values

• Host: GitHub
• URL: https://github.com/steviecurran/prediction-plot
• Owner: steviecurran
• Created: 2023-03-23T21:19:10.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-02-18T21:41:44.000Z (about 1 year ago)
• Last Synced: 2025-03-04T04:15:23.296Z (about 1 year ago)
• Topics: astrophysics, c, data-analysis, high-redshift, machine-learning, pgplot, python, statistics, tensorflow, visualization
• Language: C
• Homepage: https://ui.adsabs.harvard.edu/abs/2022MNRAS.514....1C/abstract
• Size: 244 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# prediction-plot

Code to perform machine learning (k-nearest neighbours regression) and plot the predicted versus measured values. This is all contained within kNN.py and supersedes the all of the C code above (thus not requiring me to write my own grey-scale function, etc.).

![](https://raw.githubusercontent.com/steviecurran/prediction-plot/refs/heads/main/DESI_trun.csv_df_GRZW1W2_kNN.png)

## Previous C version

Useful for large datasets, as produces a grey scale and error bars of equally binned data instead of individal points. 

Also returns a sub-plot showing the distribution of the difference in the predicted and measured values and gives the mean difference, the standard deviation and outlier fraction.

![](https://raw.githubusercontent.com/steviecurran/prediction-plot/refs/heads/main/cmp22-Fig9.png)