How to perform T-test and chi square test to my categorical variables like country, education and predict...












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I'm new to Data science. I have been working on a classification project which has columns (Sex, Age, Occupation, Marital Status, education, country, relationship,capital gain, income). Here income('<30K','>30k') is my target variable. The idea is to predict accuracy using logistic reg. I've converted the categorical columns like, Sex, Marital Status,occupation, Country, relationship, education to 1's and 0's using labelbinarizer. Then after train-test-split and feature scaling. Now when I check my accuracy its showing 100 percent accuracy and I cannot do ttest and chi_2 as the p-value remains 0.0 Am I doing something wrong here???









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    $begingroup$


    I'm new to Data science. I have been working on a classification project which has columns (Sex, Age, Occupation, Marital Status, education, country, relationship,capital gain, income). Here income('<30K','>30k') is my target variable. The idea is to predict accuracy using logistic reg. I've converted the categorical columns like, Sex, Marital Status,occupation, Country, relationship, education to 1's and 0's using labelbinarizer. Then after train-test-split and feature scaling. Now when I check my accuracy its showing 100 percent accuracy and I cannot do ttest and chi_2 as the p-value remains 0.0 Am I doing something wrong here???









    share







    New contributor




    Sathish Sash is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







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      $begingroup$


      I'm new to Data science. I have been working on a classification project which has columns (Sex, Age, Occupation, Marital Status, education, country, relationship,capital gain, income). Here income('<30K','>30k') is my target variable. The idea is to predict accuracy using logistic reg. I've converted the categorical columns like, Sex, Marital Status,occupation, Country, relationship, education to 1's and 0's using labelbinarizer. Then after train-test-split and feature scaling. Now when I check my accuracy its showing 100 percent accuracy and I cannot do ttest and chi_2 as the p-value remains 0.0 Am I doing something wrong here???









      share







      New contributor




      Sathish Sash is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I'm new to Data science. I have been working on a classification project which has columns (Sex, Age, Occupation, Marital Status, education, country, relationship,capital gain, income). Here income('<30K','>30k') is my target variable. The idea is to predict accuracy using logistic reg. I've converted the categorical columns like, Sex, Marital Status,occupation, Country, relationship, education to 1's and 0's using labelbinarizer. Then after train-test-split and feature scaling. Now when I check my accuracy its showing 100 percent accuracy and I cannot do ttest and chi_2 as the p-value remains 0.0 Am I doing something wrong here???







      machine-learning classification logistic-regression categorical-data data-science-model





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      Sathish SashSathish Sash

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