I'm trying to calculate Gaussian probability, but when I run it through my data I get ZeroDivisionError: float division by zero
here's the code:
def GaussianProbability(x, mean, std):
exponent = math.exp(-(math.pow(x-mean,2)/(2*math.pow(std,2))))
return (1 / (math.sqrt(2*math.pi) * std)) * exponent
and the complete error log:
ZeroDivisionError Traceback (most recent call last)
<ipython-input-22-b3fd5204c6fa> in <module>
----> 1 precisions_PDZ1,MAP,recalls_PDZ1,fp_rates_PDZ1 = CV_results(PDZ1_graphs,PDZ1_targets,'undirected')
<ipython-input-14-044940745269> in CV_results(list_graphs, list_targets, network_type, multi)
7 for part in tqdm(range(5)):
8
----> 9 probabilities_0,predictions = prediction(list_graphs[part], list_targets[part], network_type, multi)
10
11 if recalls == [] and fp_rates == []:
<ipython-input-12-beeed13223ea> in prediction(graph, actual_edges, network_type, multi)
11
12 for i in tqdm(range(len(X_test))):
---> 13 prob = ClassProbabilities(summaries, prob_class, X_test[i])
14 if (prob[0]+prob[1])==0:
15 # both probabilities are too low
<ipython-input-11-286b09a753e9> in ClassProbabilities(summaries, prob_class, x)
8 for i in range(len(classSummaries)): # for every attribute
9 mean, std = classSummaries[i]
---> 10 probabilities[classValue] *= GaussianProbability(x[i], mean, std)
11
12 return probabilities
<ipython-input-10-4a13cc5a69b2> in GaussianProbability(x, mean, std)
1 def GaussianProbability(x, mean, std):
----> 2 exponent = math.exp(-(math.pow(x-mean,2)/(2*math.pow(std,2))))
3 return (1 / (math.sqrt(2*math.pi) * std)) * exponent
ZeroDivisionError: float division by zero
your function needs to have an else statement when you standerdv is equal to Zero
you can see this reference it might help What is the normal distribution when standard deviation is zero?