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Neural_Network_for_MOID_Prediction
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  • 4c2bfb1af9 Jupyter notebook used for 1) training the NN, 2) evaluating its performance on the NEOPOP test set and on the real NEOs dataset main Vanessa Vichi 2024-05-12 10:24:46 +0200
  • 9d4c656139 DataFrames with the attributable elements Vanessa Vichi 2024-05-12 10:22:38 +0200
  • 35a0e891fd Pre-processed NEOs DataFrame Vanessa Vichi 2024-05-12 10:20:59 +0200
  • fb3ba5006d Saved weights of Models 1,2 after a 500-epoch training (for both models) and a 1000-epoch training for Model 1 Vanessa Vichi 2024-05-12 10:19:36 +0200
  • 2077014614 Conversion from Keplerian elements to attributable elements Vanessa Vichi 2024-05-11 10:58:40 +0200
  • 66775f772a Jupyter Notebook for pre-processing of the NEOs DataFrame Vanessa Vichi 2024-05-11 10:49:36 +0200
  • dc610efe37 Jupyter notebook for choosing the best initialization technique Vanessa Vichi 2024-05-09 10:04:46 +0200
  • b3196ff82b Jupyter notebook for evaluating the baseline performance: comparison of various metrics for the baseline model, the linear regression model and the polynomial regression model of degrees 2 and 3 Vanessa Vichi 2024-05-09 09:57:48 +0200
  • fea26621fc Jupyter notebook for splitting the NEOPOP dataset into training, validation and test (with checks over the distribution of the various parts) Vanessa Vichi 2024-05-09 09:54:30 +0200
  • 67bbd480a4 Jupyter notebook for preliminary data exploration Vanessa Vichi 2024-05-09 09:50:42 +0200
  • 66021848e3 NEOPOP DataFrame split into training, validation, test Vanessa Vichi 2024-05-09 09:47:58 +0200
  • 44da7616fa Output files of the NEOPOP run Vanessa Vichi 2024-05-09 09:44:30 +0200
  • 598f8fedd3 NEOs DataFrame Vanessa Vichi 2024-05-08 18:39:55 +0200
  • 81b4e797b3 NEOPOP DataFrame Vanessa Vichi 2024-05-08 18:38:45 +0200
  • a491844d25 Initial commit v.vichi3 2024-04-27 13:20:42 +0000