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## Smokers-Classification





  
  

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A repository of implemented ML Algorithms to classification smokers from multivariate data.





  
  

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As part of the process of learning the research problem and the data, a preliminary file of EDA is also attached.





  
  

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The task was given as part of a ML course at the university.





  
  

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The subtasks given as part of the task:





  
  

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1) Performing a pre-processing process on the data, handling NaN data and values at the edges, learning the most significant features, examining distributions of variables in the data, performing discretization and categorization.





  
  

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2) Application of 2 Supervised ML models - NN & Decision Tree, while adjusting the hyper parameters with the help of Grid-Search. Using Naptune.ai for monitoring.





  
  

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3) Application of K-Means clustering.





  
  

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4) Application of Un-supervised model with the help of integration and pre-training of NN and then application of Voting Classifier and create ensemble model.