決定木を作成する際にこのエラーが表示される理由ツリー分類器

Question

こんにちは私はDecision Tree Classifierをこのビデオに従うことで試していますHello World - 機械学習レシピ＃1 Google Developers。

ここは私のコードです。

#Import the Pandas library 
    import pandas as pd 
#Load the train and test datasets to create two DataFrames 
train_url = "http://s3.amazonaws.com/assets.datacamp.com/course/Kaggle/train.csv" train = pd.read_csv(train_url) 
#Print the head of the train and test dataframes 
train.head() 
test_url = "http://s3.amazonaws.com/assets.datacamp.com/course/Kaggle/test.csv" test = pd.read_csv(test_url) 
#Print the head of the train and test dataframes 
test.head() 
#from sklearn import tree 
from sklearn import tree 
#find the best feature to predict Survival rate 
#define X_features and Y_labels 
col_names=['Pclass','Age','SibSp','Parch'] 
X_features= train[col_names] 
#assign survial to label 
Y_labels= train.Survived 
#create a decision tree classifier 
clf=tree.DecisionTreeClassifier() 
#fit (find patterns in Data) 
clf=clf.fit(X_features, Y_labels) 
clf.predict(test[col_names]) 

ValueError Traceback (most recent call last) in() 13#Y_train_sparse=Y_labels.to_sparse() 14 # fit (find patterns in Data) ---> 15 clf=clf.fit(X_features, Y_labels) 16 #clf.predict(test[col_names])

C:\Users\nitinahu\AppData\Local\Continuum\Anaconda3\lib\site-packages\sklearn\tree\tree.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted) 152 random_state = check_random_state(self.random_state) 153 if check_input: --> 154 X = check_array(X, dtype=DTYPE, accept_sparse="csc") 155 if issparse(X): 156 X.sort_indices()

C:\Users\nitinahu\AppData\Local\Continuum\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator) 396 % (array.ndim, estimator_name)) 397 if force_all_finite: --> 398 _assert_all_finite(array) 399 400 shape_repr = _shape_repr(array.shape)

C:\Users\nitinahu\AppData\Local\Continuum\Anaconda3\lib\site-packages\sklearn\utils\validation.py in _assert_all_finite(X) 52 and not np.isfinite(X).all()): 53 raise ValueError("Input contains NaN, infinity" ---> 54 " or a value too large for %r." % X.dtype) 55 56

ValueError: Input contains NaN, infinity or a value too large for dtype('float32').

Answer 1

ちょうどuは応答になっrのすべての値をチェックし、エラーの取得。

1つまたは2つがバインドされた値を渡しているため、オーバーフローが発生しています。