62 lines
1.9 KiB
Python
62 lines
1.9 KiB
Python
import math
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def post_processing(processing_output):
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prediction = processing_output["prediction"]
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shape_reasoncode = processing_output["shape_reasoncode"]
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# grade mapping: [0.00,0.01]→M1, (0.01,0.02]→M2, … cap at M14
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if prediction < 0:
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grade = "M14"
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else:
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m = math.ceil(prediction / 0.01)
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m = max(m, 1)
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m = min(m, 14)
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grade = f"M{m}"
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# if prediction ≤ 0.04, not declined
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if prediction <= 0.04:
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return {
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"grade": grade,
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"reason_description": None
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}
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conditions = {
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'evtg04': lambda x: x < 700,
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'eads66': lambda x: x < 700,
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's004s': lambda x: x < 12,
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'mt34s': lambda x: x > 95,
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'ct320': lambda x: x <= 3,
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'us21s': lambda x: x <= 3,
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'utlmag02': lambda x: x > 300,
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'trv01': lambda x: x > 3,
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'us34s': lambda x: x > 90
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}
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reason_map = {
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'evtg04': "System Generated",
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'eads66': "System Generated",
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's004s': "Length of time on file is too short",
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'mt34s': "Too high open mortgage credit utilization recently",
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'ct320': "Insufficient payment activity",
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'us21s': "Length of time since most recent installment account has been established is too short",
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'utlmag02': "Too high revolving credit utilization over the last 24 months",
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'trv01': "Recency of a balance overlimit on a bankcard account",
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'us34s': "Too high open unsecured installment credit utilization recently"
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}
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for item in shape_reasoncode:
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feat = item["feature"]
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val = item["value"]
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cond = conditions.get(feat)
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if cond and cond(val):
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return {
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"grade": grade,
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"reason_description": reason_map[feat]
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}
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return {
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"grade": grade,
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"reason_description": None
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}
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