Decision Tree.py

#!/usr/bin/env python
# coding: utf-8

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import pandas as pd
df = pd.read_csv("salaries.csv")
df.head()


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inputs = df.drop("salary_more_then_100k", axis = "columns")
targets = df["salary_more_then_100k"]


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inputs


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from sklearn.preprocessing import LabelEncoder


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le_company = LabelEncoder()
le_job = LabelEncoder()
le_degree = LabelEncoder()


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inputs["company_n"] = le_company.fit_transform(inputs["company"])
inputs["job_n"] = le_job.fit_transform(inputs["job"])
inputs["degree_n"] = le_degree.fit_transform(inputs["degree"])
inputs.head()


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inputs_n = inputs.drop(["job","degree", "company"], axis = "columns")
inputs_n


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from sklearn import tree


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model = tree.DecisionTreeClassifier()


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model.fit(inputs_n,targets)


# models.score(inputs_n, targets)

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model.score(inputs_n,targets)


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model.predict([[1,2,1]])


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