Created
May 19, 2015 20:43
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NLP NaiveBaise , Python
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| __author__ = 'Mohamed_Ramadan_PC' | |
| f1 =open('E:\\healthy.txt','r+') | |
| f2 =open('E:\\unhealthy.txt','r+') | |
| f3=open('E:\\NoOfHealthy.txt','r+') | |
| f4=open('E:\\NoOfUnHealthy.txt','r+') | |
| def learn(food,sort): | |
| TheMeal=food.split(" ") | |
| for meal in TheMeal: | |
| if sort==1: | |
| f1.write(meal+" ") | |
| x=+1 | |
| else : | |
| f2.write(meal+" ") | |
| def predict(meal,laplace): | |
| f1 =open('E:\\healthy.txt','r+') | |
| f2 =open('E:\\unhealthy.txt','r+') | |
| t1=f1.read() | |
| healthy_length=t1.split(" ") | |
| t2=f2.read() | |
| unhealthy_length=t2.split(" ") | |
| f3.write('{}'.format(len(healthy_length)-1)) | |
| f4.write('{}'.format(len(unhealthy_length)-1)) | |
| healthy_counter=len(healthy_length)-1 | |
| unhealthy_counter=len(unhealthy_length)-1 | |
| all_food=healthy_counter + unhealthy_counter | |
| p_h=(healthy_counter+laplace)/(all_food*1.0+laplace*2) | |
| p_unh=(unhealthy_counter+laplace)/(all_food*1.0+laplace*2) | |
| print("total foods= {}".format(all_food)) | |
| print("Healthy foods= {}".format(healthy_counter)) | |
| print("Un-Healthy foods= {}".format(unhealthy_counter)) | |
| print("p_h= {}".format(p_h)) | |
| print("p_unh= {}".format(p_unh)) | |
| print("Healthy words= {}".format(healthy_length)) | |
| print("Un-healthy words= {}".format(unhealthy_length)) | |
| meals=meal.split(" ") | |
| p_f_h=0.1 | |
| p_f_unh=0.1 | |
| for food in meals: | |
| if food in healthy_length: | |
| p_f_unh*=(1*1.0+laplace)/(unhealthy_counter+laplace*all_food) | |
| else : | |
| p_f_h*=(1*1.0+laplace)/(healthy_counter+laplace*all_food) | |
| print("p_f_h= {}".format(p_f_h)) | |
| print("p_f_unh= {}".format(p_f_unh)) | |
| p_h_f=(p_h*p_f_h)/(p_f_h*p_h+p_f_unh*p_unh) | |
| p_unh_f=(p_unh*p_f_unh)/(p_f_h*p_h+p_f_unh*p_unh) | |
| print("p_h_f= {}".format(p_h_f)) | |
| print("p_unh_f= {}".format(p_unh_f)) | |
| if(p_h_f>p_unh_f): | |
| print("This meal is Classified as Healthy meal ") | |
| else : | |
| print("This meal is Classified as Un-Healthy meal ") | |
| learn("tomato",1) | |
| learn("vegetable",1) | |
| learn("Bread rice macaron cream_chante",0) | |
| learn("tost",1) | |
| f1.close() | |
| f2.close() | |
| predict("rice vegetable tomato",1) |
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