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# Plotabit
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# Plotabit
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Dataset link: https://www.kaggle.com/datasets/fedesoriano/stellar-classification-dataset-sdss17
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Dataset link: https://www.kaggle.com/datasets/fedesoriano/stellar-classification-dataset-sdss17
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Deep Learning: https://machinelearningmastery.com/tutorial-first-neural-network-python-keras/
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## Columns
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## Columns
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|Keep |Not sure |Skip |
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|Keep |Skip |
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|:-----------:|:----------:|:----------:|
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|:-----------:|:----------:|
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|alpha |field_ID |obj_ID |
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|alpha |obj_ID |
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|delta | |run_ID |
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|delta |run_ID |
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|u | |rerun_ID |
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|u |rerun_ID |
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|g | |plate |
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|g |plate |
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|r | |MJD |
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|r |MJD |
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|i | |fiber_ID |
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|i |fiber_ID |
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|z | | |
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|z | |
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|redshift | | |
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|redshift | |
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## Analysis
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- [ ] Train models with just 20000 "GALAXY" class (has an impact?)
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- [ ] Which model is the best, ratio learn_time/precision
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- [ ] Can we drop more categories and have same results (useless data?)
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