abhmalik / halo_conc-regression-ML

In this code, we will carry out a simple regression task. For this we will first download a public dark matter halo catalogue from the Bolshoi simulation. We will then use the Pandas library to analyse this halo catalogue and to identify correlation between different halo properties. In the next step, we will use the Scikit-Learn library to predict the halo concentration from the other halo properties. For this we will test simple linear regression, a decision tree, and random forests. Finally, we will determine which regression algorithm performs best with respect to the test data set.

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Predicting Halo Concentration Using Machine Learning

In this code, we will carry out a simple regression task. For this we will first download a public dark matter halo catalogue from the Bolshoi simulation. We will then use the Pandas library to analyse this halo catalogue and to identify correlation between different halo properties. In the next step, we will use the Scikit-Learn library to predict the halo concentration from the other halo properties. For this we will test simple linear regression, a decision tree, and random forests. Finally, we will determine which regression algorithm performs best with respect to the test data set.

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In this code, we will carry out a simple regression task. For this we will first download a public dark matter halo catalogue from the Bolshoi simulation. We will then use the Pandas library to analyse this halo catalogue and to identify correlation between different halo properties. In the next step, we will use the Scikit-Learn library to predict the halo concentration from the other halo properties. For this we will test simple linear regression, a decision tree, and random forests. Finally, we will determine which regression algorithm performs best with respect to the test data set.


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