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Browse files
app.py
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@@ -14,6 +14,11 @@ from sklearn.preprocessing import LabelEncoder
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from sklearn.preprocessing import OneHotEncoder
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# TODO: Implement MBTI features
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def greet(name, body_profile_type):
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user_df = {}
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from sklearn.preprocessing import OneHotEncoder
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# TODO: Implement MBTI features
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# Testing: curl -X POST https://debisoft-junction.hf.space/api/predict -H 'Content-Type: application/json' -d '{"data": [<name>,<body_profile_type>]}
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# body_profile_type => [0-4]
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# Eg. curl -X POST https://debisoft-junction.hf.space/api/predict -H 'Content-Type: application/json' -d '{"data": ["David",4]}
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# Adapted from https://www.geeksforgeeks.org/predict-tinder-matches-with-machine-learning/
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def greet(name, body_profile_type):
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user_df = {}
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