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Internship-diabetes-prediction

The following project is an internship task assign by Meriskill to train a model to predict the diabetes of the women as this dataset contains only a data of women. The steps invloved in this project are as follows :

  • 1)Reading CSV Files
  • 2)Checking Null values and Filling Them.(Data Cleaning)
  • 3)Visualizations : To know the relationship between independent and dependent variable.
  • 4)Splitting the data and scaling it
  • 5)Identifying input columns and target columns.
  • 6)Logistic regression
  • 7)Random Forest
  • 8)Gradient Boosting
  • 9)Comparing different Model and Selecting Best One.
  • 10)Using Best Model on Custom data
  • 11)Conclusion

The following are the conclusion :

  • 1)Dataset is small that's why model is overfitting in first attempt.
  • 2)The Dataset can include data like diet, difficulty in walking,education about diabetes,etc.
  • 3)Our Model is giving 81% accuracy that is good in such problems beacuse the bilogical law are not perfect.
  • 4)With increase in dataset our model can reach accuracy of 90%.