File size: 2,253 Bytes
1d3a987 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
import joblib
import pandas as pd
with open("scaler.joblib", 'rb') as f:
scaler = joblib.load(f)
# data = {
# "Pregnancies": [6],
# "Glucose": [148]
# "BloodPressure": [72],
# "SkinThickness": [35]
# "BMI": [33.6],
# "DiabetesPedigreeFunction": [0.627]
# "Age": [50]
# }
# df = pd.DataFrame(data)
outs = scaler.transform([[6, 148, 72, 35, 33.6, 0.627, 50]])
for i in outs[0]:
print(i)
# def is_number(text):
# try:
# # Try to convert the text to a float
# float(text)
# return True
# except ValueError:
# # If conversion fails, it's not a number
# return False
# inp = "1.5"
# if is_number(inp):
# print(int(inp.split('.')[0]))
# print(int(1.5))
# def diabetic_pedigree_function(mother, father, siblings):
# """
# Calculate a scaled Diabetic Pedigree Function (DPF) for an individual,
# aiming for an output range of approximately (0.078, 2.42).
# Parameters:
# mother (int): 1 if the mother has diabetes, 0 otherwise.
# father (int): 1 if the father has diabetes, 0 otherwise.
# siblings (list): A list of 0s and 1s representing siblings' diabetes status.
# Returns:
# float: The scaled diabetic pedigree function score.
# """
# # Assign weights to each family member
# mother_weight = 0.5
# father_weight = 0.5
# sibling_weight = 0.25
# # Calculate the weighted contributions
# family_history = (mother * mother_weight) + (father * father_weight) + (sum(siblings) * sibling_weight)
# # Add a scaling factor to shift the range
# scaling_factor = 1.2
# bias = 0.078 # Minimum value in the desired range
# # Final scaled DPF score
# dpf_score = family_history * scaling_factor + bias
# return round(dpf_score, 3) # Rounded for clarity
# # Example usage:
# mother_history = 1 # Mother has diabetes
# father_history = 0 # Father doesn't have diabetes
# siblings_history = [1, 0, 0] # One sibling has diabetes, two do not
# dpf = diabetic_pedigree_function(mother_history, father_history, siblings_history)
# print(f"The Diabetic Pedigree Function score is: {dpf}")
|