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In [12]:
import numpy as np
import pandas as pd

from pgmpy.models import BayesianModel
from pgmpy.estimators import MaximumLikelihoodEstimator
from pgmpy.inference import VariableElimination
import csv
lines=list(csv.reader(open('/home/jss/Documents/datasets/71.csv',"r")))
attributes=lines[0]
heartDisease=pd.read_csv('/home/jss/Documents/datasets/72.csv',names=attributes)
heartDisease=heartDisease.replace('?',np.nan)
print("the dataset names")
print(heartDisease.head())
print("the datatypes and features")
print(heartDisease.dtypes)
model=BayesianModel([('age','trestbps'),('age','fbs'),('sex','trestbps'),
                    ('exang','trestbps'),('trestbps','heartdisease'),('fbs','heartdisease'),
                    ('heartdisease','restecg'),('heartdisease','thalach'),('heartdisease','chol')])
print("learning from CPDs of MaximumLIlelihoodEstimator")
model.fit(heartDisease,estimator=MaximumLikelihoodEstimator)
print("Inferencing from Variable elimination")
HeartDisease_infer=VariableElimination(model)
print("probablity when trestbps and fbs is given")
q=HeartDisease_infer.query(variables=['heartdisease'],evidence={'trestbps':4,'fbs':0})
print(q['heartdisease'])
the dataset names age sex cp trestbps chol fbs restecg thalach exang oldpeak \ 0 63.0 1.0 1.0 145.0 233.0 1.0 2.0 150.0 0.0 2.3 1 67.0 1.0 4.0 160.0 286.0 0.0 2.0 108.0 1.0 1.5 2 67.0 1.0 4.0 120.0 229.0 0.0 2.0 129.0 1.0 2.6 3 37.0 1.0 3.0 130.0 250.0 0.0 0.0 187.0 0.0 3.5 4 41.0 0.0 2.0 130.0 204.0 0.0 2.0 172.0 0.0 1.4 slope ca thal heartdisease 0 3.0 0.0 6.0 0 1 2.0 3.0 3.0 2 2 2.0 2.0 7.0 1 3 3.0 0.0 3.0 0 4 1.0 0.0 3.0 0 the datatypes and features age float64 sex float64 cp float64 trestbps float64 chol float64 fbs float64 restecg float64 thalach float64 exang float64 oldpeak float64 slope float64 ca object thal object heartdisease int64 dtype: object learning from CPDs of MaximumLIlelihoodEstimator Inferencing from Variable elimination probablity when trestbps and fbs is given +----------------+---------------------+ | heartdisease | phi(heartdisease) | +================+=====================+ | heartdisease_0 | 1.0000 | +----------------+---------------------+ | heartdisease_1 | 0.0000 | +----------------+---------------------+ | heartdisease_2 | 0.0000 | +----------------+---------------------+ | heartdisease_3 | 0.0000 | +----------------+---------------------+ | heartdisease_4 | 0.0000 | +----------------+---------------------+
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