class_docstr: The Gaussian Naive Bayes classifier. 
class_docstr_tok: ["The","Gaussian","Naive","Bayes","classifier","."]
docstr: Calculate the prior of class c
  (samples where class == c / total number of samples)
docstr_tok: ["Calculate","the","prior","of","class","c","(","samples","where","class","==","c","\/","total","number","of","samples",")"]
code: def _calculate_prior(self, c):
      """Calculate the prior of class c
      (samples where class == c / total number of samples)"""
      frequency = np.mean(self.y == c)
      return frequency
  
file_path: ML-From-Scratch/mlfromscratch/supervised_learning/naive_bayes.py
imports: from __future__ import division, print_function
  import numpy
  import math
  from mlfromscratch.utils import train_test_split, normalize
  from mlfromscratch.utils import Plot, accuracy_score
label_desc: Use image node_id 3 for calling the NaiveBayes obj's underlying member method code with example usage: obj._calculate_prior(c) and returns: frequency