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???
machine-learning classification logistic-regression categorical-data data-science-model
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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???
machine-learning classification logistic-regression categorical-data data-science-model
New contributor
$endgroup$
add a comment |
$begingroup$
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???
machine-learning classification logistic-regression categorical-data data-science-model
New contributor
$endgroup$
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
machine-learning classification logistic-regression categorical-data data-science-model
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asked 6 mins ago
Sathish SashSathish Sash
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