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model.py
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model.py
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from tkinter import *
from tkinter import messagebox
import numpy as np
import pandas as pd
import pickle
l1 = ['itching', 'skin_rash', 'nodal_skin_eruptions', 'continuous_sneezing', 'shivering', 'chills', 'joint_pain',
'stomach_pain', 'acidity', 'ulcers_on_tongue', 'muscle_wasting', 'vomiting', 'burning_micturition', 'spotting_ urination', 'fatigue',
'weight_gain', 'anxiety', 'cold_hands_and_feets', 'mood_swings', 'weight_loss', 'restlessness', 'lethargy', 'patches_in_throat',
'irregular_sugar_level', 'cough', 'sunken_eyes', 'breathlessness', 'sweating', 'dehydration', 'indigestion',
'headache', 'yellowish_skin', 'dark_urine', 'nausea', 'loss_of_appetite', 'pain_behind_the_eyes', 'back_pain', 'constipation',
'abdominal_pain', 'diarrhoea', 'mild_fever', 'yellow_urine', 'yellowing_of_eyes', 'acute_liver_failure', 'fluid_overload',
'swelling_of_stomach', 'swelled_lymph_nodes', 'malaise', 'blurred_and_distorted_vision', 'phlegm', 'throat_irritation',
'redness_of_eyes', 'sinus_pressure', 'runny_nose', 'congestion', 'chest_pain', 'weakness_in_limbs', 'fast_heart_rate',
'pain_during_bowel_movements', 'pain_in_anal_region', 'bloody_stool', 'irritation_in_anus', 'neck_pain', 'dizziness', 'cramps',
'bruising', 'obesity', 'swollen_legs', 'swollen_blood_vessels', 'puffy_face_and_eyes', 'enlarged_thyroid', 'brittle_nails',
'swollen_extremeties', 'excessive_hunger', 'extra_marital_contacts', 'drying_and_tingling_lips', 'slurred_speech', 'knee_pain', 'hip_joint_pain',
'muscle_weakness', 'stiff_neck', 'swelling_joints', 'movement_stiffness', 'spinning_movements', 'loss_of_balance', 'unsteadiness', 'weakness_of_one_body_side',
'loss_of_smell', 'bladder_discomfort', 'foul_smell_of urine', 'continuous_feel_of_urine', 'passage_of_gases', 'internal_itching', 'toxic_look_(typhos)',
'depression', 'irritability', 'muscle_pain', 'altered_sensorium', 'red_spots_over_body', 'belly_pain', 'abnormal_menstruation', 'dischromic _patches',
'watering_from_eyes', 'increased_appetite', 'polyuria', 'family_history', 'mucoid_sputum', 'rusty_sputum', 'lack_of_concentration', 'visual_disturbances',
'receiving_blood_transfusion', 'receiving_unsterile_injections', 'coma', 'stomach_bleeding', 'distention_of_abdomen', 'history_of_alcohol_consumption',
'fluid_overload', 'blood_in_sputum', 'prominent_veins_on_calf', 'palpitations', 'painful_walking', 'pus_filled_pimples', 'blackheads', 'scurring', 'skin_peeling',
'silver_like_dusting', 'small_dents_in_nails', 'inflammatory_nails', 'blister', 'red_sore_around_nose', 'yellow_crust_ooze']
disease = ['Fungal infection', 'Allergy', 'GERD', 'Chronic cholestasis', 'Drug Reaction',
'Peptic ulcer diseae', 'AIDS', 'Diabetes', 'Gastroenteritis', 'Bronchial Asthma', 'Hypertension',
' Migraine', 'Cervical spondylosis',
'Paralysis (brain hemorrhage)', 'Jaundice', 'Malaria', 'Chicken pox', 'Dengue', 'Typhoid', 'hepatitis A',
'Hepatitis B', 'Hepatitis C', 'Hepatitis D', 'Hepatitis E', 'Alcoholic hepatitis', 'Tuberculosis',
'Common Cold', 'Pneumonia', 'Dimorphic hemmorhoids(piles)',
'Heartattack', 'Varicoseveins', 'Hypothyroidism', 'Hyperthyroidism', 'Hypoglycemia', 'Osteoarthristis',
'Arthritis', '(vertigo) Paroymsal Positional Vertigo', 'Acne', 'Urinary tract infection', 'Psoriasis',
'Impetigo']
# TESTING DATA
tr = pd.read_csv("Testing.csv")
tr.replace({'prognosis': {'Fungal infection': 0, 'Allergy': 1, 'GERD': 2, 'Chronic cholestasis': 3, 'Drug Reaction': 4,
'Peptic ulcer diseae': 5, 'AIDS': 6, 'Diabetes ': 7, 'Gastroenteritis': 8, 'Bronchial Asthma': 9, 'Hypertension ': 10,
'Migraine': 11, 'Cervical spondylosis': 12,
'Paralysis (brain hemorrhage)': 13, 'Jaundice': 14, 'Malaria': 15, 'Chicken pox': 16, 'Dengue': 17, 'Typhoid': 18, 'hepatitis A': 19,
'Hepatitis B': 20, 'Hepatitis C': 21, 'Hepatitis D': 22, 'Hepatitis E': 23, 'Alcoholic hepatitis': 24, 'Tuberculosis': 25,
'Common Cold': 26, 'Pneumonia': 27, 'Dimorphic hemmorhoids(piles)': 28, 'Heart attack': 29, 'Varicose veins': 30, 'Hypothyroidism': 31,
'Hyperthyroidism': 32, 'Hypoglycemia': 33, 'Osteoarthristis': 34, 'Arthritis': 35,
'(vertigo) Paroymsal Positional Vertigo': 36, 'Acne': 37, 'Urinary tract infection': 38, 'Psoriasis': 39,
'Impetigo': 40}}, inplace=True)
X_test = tr[l1]
y_test = tr[["prognosis"]]
np.ravel(y_test)
# TRAINING DATA
df = pd.read_csv("Training.csv")
df.replace({'prognosis': {'Fungal infection': 0, 'Allergy': 1, 'GERD': 2, 'Chronic cholestasis': 3, 'Drug Reaction': 4,
'Peptic ulcer diseae': 5, 'AIDS': 6, 'Diabetes ': 7, 'Gastroenteritis': 8, 'Bronchial Asthma': 9, 'Hypertension ': 10,
'Migraine': 11, 'Cervical spondylosis': 12,
'Paralysis (brain hemorrhage)': 13, 'Jaundice': 14, 'Malaria': 15, 'Chicken pox': 16, 'Dengue': 17, 'Typhoid': 18, 'hepatitis A': 19,
'Hepatitis B': 20, 'Hepatitis C': 21, 'Hepatitis D': 22, 'Hepatitis E': 23, 'Alcoholic hepatitis': 24, 'Tuberculosis': 25,
'Common Cold': 26, 'Pneumonia': 27, 'Dimorphic hemmorhoids(piles)': 28, 'Heart attack': 29, 'Varicose veins': 30, 'Hypothyroidism': 31,
'Hyperthyroidism': 32, 'Hypoglycemia': 33, 'Osteoarthristis': 34, 'Arthritis': 35,
'(vertigo) Paroymsal Positional Vertigo': 36, 'Acne': 37, 'Urinary tract infection': 38, 'Psoriasis': 39,
'Impetigo': 40}}, inplace=True)
X = df[l1]
y = df[["prognosis"]]
np.ravel(y)
def message():
if (Symptom1.get() == "None" and Symptom2.get() == "None" and Symptom3.get() == "None" and Symptom4.get() == "None" and Symptom5.get() == "None"):
messagebox.showinfo("OPPS!!", "ENTER SYMPTOMS PLEASE")
else:
DecisionTreeClassifier()
def DecisionTreeClassifier():
from sklearn.svm import SVC
gnb = SVC()
gnb.fit(X, np.ravel(y))
# from sklearn.tree import DecisionTreeClassifier
# gnb = DecisionTreeClassifier()
# gnb.fit(X, np.ravel(y))
filename = 'finalized_model.pickle'
pickle.dump(gnb, open(filename, 'wb'))
from sklearn.metrics import accuracy_score
y_pred = gnb.predict(X_test)
print('Accuracy Score', accuracy_score(y_test, y_pred))
print(accuracy_score(y_test, y_pred, normalize=False))
psymptoms = [Symptom1.get(), Symptom2.get(), Symptom3.get(),
Symptom4.get(), Symptom5.get()]
l2 = []
for k in range(0, len(l1)):
for z in psymptoms:
if(z == l1[k]):
l2[k] = 1
inputtest = [l2]
print(inputtest)
predict = gnb.predict(inputtest)
print(predict)
predicted = predict[0]
h = 'no'
for a in range(0, len(disease)):
if(disease[predicted] == disease[a]):
h = 'yes'
break
if (h == 'yes'):
t3.delete("1.0", END)
t3.insert(END, disease[a])
else:
t3.delete("1.0", END)
t3.insert(END, "No Disease")
root = Tk()
root.title(" Disease Prediction From Symptoms")
root.configure()
Symptom1 = StringVar()
Symptom1.set(None)
Symptom2 = StringVar()
Symptom2.set(None)
Symptom3 = StringVar()
Symptom3.set(None)
Symptom4 = StringVar()
Symptom4.set(None)
Symptom5 = StringVar()
Symptom5.set(None)
w2 = Label(root, justify=LEFT, text=" Disease Prediction From Symptoms ")
w2.config(font=("Elephant", 30))
w2.grid(row=1, column=0, columnspan=2, padx=100)
NameLb1 = Label(root, text="")
NameLb1.config(font=("Elephant", 20))
NameLb1.grid(row=5, column=1, pady=10, sticky=W)
S1Lb = Label(root, text="Symptom 1")
S1Lb.config(font=("Elephant", 15))
S1Lb.grid(row=7, column=1, pady=10, sticky=W)
S2Lb = Label(root, text="Symptom 2")
S2Lb.config(font=("Elephant", 15))
S2Lb.grid(row=8, column=1, pady=10, sticky=W)
S3Lb = Label(root, text="Symptom 3")
S3Lb.config(font=("Elephant", 15))
S3Lb.grid(row=9, column=1, pady=10, sticky=W)
S4Lb = Label(root, text="Symptom 4")
S4Lb.config(font=("Elephant", 15))
S4Lb.grid(row=10, column=1, pady=10, sticky=W)
S5Lb = Label(root, text="Symptom 5")
S5Lb.config(font=("Elephant", 15))
S5Lb.grid(row=11, column=1, pady=10, sticky=W)
lr = Button(root, text="Predict", height=2, width=20, command=message)
lr.config(font=("Elephant", 15))
lr.grid(row=15, column=1, pady=20)
OPTIONS = sorted(l1)
S1En = OptionMenu(root, Symptom1, *OPTIONS)
S1En.grid(row=7, column=2)
S2En = OptionMenu(root, Symptom2, *OPTIONS)
S2En.grid(row=8, column=2)
S3En = OptionMenu(root, Symptom3, *OPTIONS)
S3En.grid(row=9, column=2)
S4En = OptionMenu(root, Symptom4, *OPTIONS)
S4En.grid(row=10, column=2)
S5En = OptionMenu(root, Symptom5, *OPTIONS)
S5En.grid(row=11, column=2)
NameLb = Label(root, text="")
NameLb.config(font=("Elephant", 20))
NameLb.grid(row=13, column=1, pady=10, sticky=W)
NameLb = Label(root, text="")
NameLb.config(font=("Elephant", 15))
NameLb.grid(row=18, column=1, pady=10, sticky=W)
t3 = Text(root, height=2, width=30)
t3.config(font=("Elephant", 20))
t3.grid(row=20, column=1, padx=10)
root.mainloop()