Question

im试图使用树分类器为疾病症状创建一个简单的分类。我已经尝试过使用sklearn树分类器。它给出以下错误。我的代码和错误都在那里。有什么建议吗？

import numpy as np
from sklearn import tree
symptoms = [['flat face','poor moro','hypotonia'],['small head','small jaw','overlapping fingers'], ['small eyes','cleft lip','cleft palate']]
lables = [['Trisomy 21'],['Trisomy 18'],['Trisomy 13']]
classify = tree.DecisionTreeClassifier()
classify = classify.fit(symptoms, lables)

它出现以下错误

ValueError                                Traceback (most recent call last)
<ipython-input-25-0f2c956618c2> in <module>
      4 lables = [['Trisomy 21'],['Trisomy 18'],['Trisomy 13']]
      5 classify = tree.DecisionTreeClassifier()
----> 6 classify = classify.fit(symptoms, lables)

c:\users\admin\appdata\local\programs\python\python36\lib\site-packages\sklearn\tree\tree.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
    799             sample_weight=sample_weight,
    800             check_input=check_input,
--> 801             X_idx_sorted=X_idx_sorted)
    802         return self
    803 

c:\users\admin\appdata\local\programs\python\python36\lib\site-packages\sklearn\tree\tree.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
    114         random_state = check_random_state(self.random_state)
    115         if check_input:
--> 116             X = check_array(X, dtype=DTYPE, accept_sparse="csc")
    117             y = check_array(y, ensure_2d=False, dtype=None)
    118             if issparse(X):

c:\users\admin\appdata\local\programs\python\python36\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    525             try:
    526                 warnings.simplefilter('error', ComplexWarning)
--> 527                 array = np.asarray(array, dtype=dtype, order=order)
    528             except ComplexWarning:
    529                 raise ValueError("Complex data not supported\n"

c:\users\admin\appdata\local\programs\python\python36\lib\site-packages\numpy\core\numeric.py in asarray(a, dtype, order)
    499 
    500     """
--> 501     return array(a, dtype, copy=False, order=order)
    502 
    503 

ValueError: could not convert string to float: 'flat face'

Answer 1

您需要使用label encoder对字符串值进行编码。以下将满足您的要求：

import numpy as np
from sklearn import tree
from sklearn.preprocessing import LabelEncoder
symptoms = [['flat face','poor moro','hypotonia'],['small head','small jaw','overlapping fingers'], ['small eyes','cleft lip','cleft palate']]
lables = [['Trisomy 21'],['Trisomy 18'],['Trisomy 13']]
df = pd.concat([pd.DataFrame(symptoms), pd.DataFrame(lables)], axis=1)
x_cols = ['sym1', 'sym2', 'sym3']
y_col = 'target'
df.columns = x_cols + [y_col]
df = df.apply(LabelEncoder().fit_transform)
classify = tree.DecisionTreeClassifier()
classify.fit(df[x_cols].values, df[y_col].values)

Sklearn树分类数据

1 个答案: