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Binary classification of start as pulsar or non- pulsar based on observation results using CatBoost, XGBoost and LGBM.

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BinaryPulsarStarClassification

Binary classification of start as pulsar or non- pulsar based on observation results using CatBoost, XGBoost and LGBM.

Features taken into consideration:

  • Mean_Integrated: Mean of Observations.
  • SD: Standard deviation of Observations.
  • EK: Excess kurtosis of Observations.
  • Skewness: In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. Skewness of Observations.
  • Mean_DMSNR_Curve: Mean of DM SNR CURVE of Observations.
  • SD_DMSNR_Curve: Standard deviation of DM SNR CURVE of Observations.
  • EK_DMSNR_Curve: Excess kurtosis of DM SNR CURVE of Observations.
  • Skewness_DMSNR_Curve: Skewness of DM SNR CURVE of Observations

Kaggle Competition: https://www.kaggle.com/competitions/playground-series-s3e10
Kaggle Notebook: https://www.kaggle.com/code/mnokno/pulsar-classification-for-class-prediction

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Binary classification of start as pulsar or non- pulsar based on observation results using CatBoost, XGBoost and LGBM.

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