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Use decision trees to prepare a model on fraud data treating those who have taxable_income <= 30000 as "Risky" and others are "Good" Data Description : Undergrad : person is under graduated or not Marital.Status : marital status of a person Taxable.Income : Taxable income is the amount of how much tax an individual owes to the government Work Experience : Work experience of an individual person Urban : Whether that person belongs to urban area or not

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pandas numpy decision-tree-classifier entropy-measures ginnni ginni-function random-forest eda dummies

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Assignment-decision_trees-fraudcheck

Use decision trees to prepare a model on fraud data treating those who have taxable_income <= 30000 as "Risky" and others are "Good" Data Description : Undergrad : person is under graduated or not Marital.Status : marital status of a person Taxable.Income : Taxable income is the amount of how much tax an individual owes to the government Work Experience : Work experience of an individual person Urban : Whether that person belongs to urban area or not

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