Python – 来自字典的随机样本训练和测试数据

有时，在使用机器学习算法时，我们可能会遇到需要随机区分训练和测试数据的问题。这是非常常见的问题，机器学习领域需要解决方案。本文讨论了在不使用外部库的情况下解决此问题的方法。

方法：使用keys() + random.randint() + 计算
这个问题可以通过以上功能的组合来解决。在此，我们执行使用 randint() 从使用 keys() 提取的密钥中提取随机密钥的任务。执行逻辑计算以获得分离的测试和训练数据。

# Python3 code to demonstrate working of 
# Random Sample Training and Test Data
# Using keys() + randint() + computations
import random
  
# initializing dictionary
test_dict = {'gfg' : 4, 'is' : 12, 'best' : 6, 'for' : 7, 'geeks' : 10}
  
# printing original dictionary
print("The original dictionary is : " + str(test_dict))
  
# initializing ratio
test = 40
training = 60
  
# Random Sample Training and Test Data
# Using keys() + randint() + computations
key_list = list(test_dict.keys())
  
test_key_count = int((len(key_list) / 100) * test)
test_keys = [random.choice(key_list) for ele in range(test_key_count)]
train_keys = [ele for ele in key_list if ele not in test_keys]
  
testing_dict = dict((key, test_dict[key]) for key in test_keys 
                                        if key in test_dict) 
training_dict = dict((key, test_dict[key]) for key in train_keys 
                                        if key in test_dict) 
  
# printing result 
print("The testing dictionary is : " + str(testing_dict)) 
print("The training dictionary is : " + str(training_dict)) 

输出 ：

The original dictionary is : {‘is’: 12, ‘gfg’: 4, ‘best’: 6, ‘for’: 7, ‘geeks’: 10}
The testing dictionary is : {‘is’: 12, ‘for’: 7}
The training dictionary is : {‘gfg’: 4, ‘best’: 6, ‘geeks’: 10}