Untitled

From Torrid Pheasant, 10 Months ago, written in Plain Text, viewed 389 times.
URL http://codebin.org/view/38cf0347 Embed
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  1. import pandas as pd
  2. from sklearn.tree import DecisionTreeClassifier
  3.  
  4. data = pd.read_csv('/datasets/heart.csv')
  5. features = data.drop(['target'], axis=1)
  6. target = data['target']
  7.  
  8. scores = []
  9.  
  10. # зададим размер блока, если их всего три
  11. sample_size = int(len(data)/3)
  12.  
  13. for i in range(0, len(data), sample_size):
  14.     valid_indexes = data.iloc[i: i+sample_size].index
  15.     train_indexes = (data.iloc[:i] + data.iloc[i + sample_size:]).index
  16.                 # разбейте переменные features и target на выборки features_train, target_train, features_valid, target_valid
  17.     # < напишите код здесь >
  18.     features_valid = features.iloc[valid_indexes]
  19.     target_valid = target.iloc[valid_indexes]
  20.     features_train = features.iloc[train_indexes]
  21.     target_train = target.iloc[train_indexes]
  22.  
  23.     model = DecisionTreeClassifier(random_state=0)
  24.     model = model.fit(features_train, target_train)
  25.     score = model.score(features_valid, target_valid) # < оцените качество модели >
  26.    
  27.     scores.append(score)
  28. scores = pd.Series(scores)  
  29. final_score = scores.mean()
  30. print('Средняя оценка качества модели:', final_score)

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