X和Y矩阵的尺寸不兼容

时间:2019-10-16 15:09:34

标签: python scikit-learn sklearn-pandas

我想知道我在哪里错了,我得到了错误

Traceback (most recent call last):
  File "main.py", line 37, in <module>
    y_pred = knn.predict(X_test)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/neighbors/classification.py", line149, in predict
    neigh_dist, neigh_ind = self.kneighbors(X)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/neighbors/base.py", line 434, in kneighbors
    **kwds))
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/metrics/pairwise.py", line 1448, in pairwise_distances_chunked
    n_jobs=n_jobs, **kwds)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/metrics/pairwise.py", line 1588, in pairwise_distances
    return _parallel_pairwise(X, Y, func, n_jobs, **kwds)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/metrics/pairwise.py", line 1206, in _parallel_pairwise
    return func(X, Y, **kwds)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/metrics/pairwise.py", line 232, ineuclidean_distances
    X, Y = check_pairwise_arrays(X, Y)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/metrics/pairwise.py", line 125, incheck_pairwise_arrays
    X.shape[1], Y.shape[1]))
ValueError: Incompatible dimension for X and Y matrices: X.shape[1] == 38 while Y.shape[1] == 43

我是AI新手,在互联网上找不到能真正解决此问题的任何东西,任何评论都表示赞赏。这是我的代码

from sklearn.preprocessing import OneHotEncoder
from sklearn import metrics 
from sklearn.neighbors import KNeighborsClassifier 
from sklearn.model_selection import train_test_split
import pandas as pd

fileName = "breast-cancer-fixed.csv";

df = pd.read_csv(fileName)

X = df[df.columns[:-1]] 
y = df[df.columns[-1]]  

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1) 

X_train = OneHotEncoder().fit_transform(X_train)
X_test = OneHotEncoder().fit_transform(X_test)

knn = KNeighborsClassifier(n_neighbors=3) 
knn.fit(X_train, y_train) 

y_pred = knn.predict(X_test)
print("kNN model accuracy:", metrics.accuracy_score(y_test, y_pred)) 

我的csv很大,我无法将其上传到这里,所以我在其中放入了一个小片段

age,menopause,tumor-size,inv-nodes,node-caps,deg-malig,breast,breast-quad,irradiat,Class
40-49,premeno,15-19,0-2,yes,3,right,left_up,no,recurrence-events
50-59,ge40,15-19,0-2,no,1,right,central,no,no-recurrence-events
50-59,ge40,35-39,0-2,no,2,left,left_low,no,recurrence-events
40-49,premeno,35-39,0-2,yes,3,right,left_low,yes,no-recurrence-events
40-49,premeno,30-34,3-5,yes,2,left,right_up,no,recurrence-events
50-59,premeno,25-29,3-5,no,2,right,left_up,yes,no-recurrence-events
50-59,ge40,40-44,0-2,no,3,left,left_up,no,no-recurrence-events
40-49,premeno,10-14,0-2,no,2,left,left_up,no,no-recurrence-events
40-49,premeno,0-4,0-2,no,2,right,right_low,no,no-recurrence-events
40-49,ge40,40-44,15-17,yes,2,right,left_up,yes,no-recurrence-events
50-59,premeno,25-29,0-2,no,2,left,left_low,no,no-recurrence-events
60-69,ge40,15-19,0-2,no,2,right,left_up,no,no-recurrence-events

如果我摆脱了最后两行代码(预测代码),它也可以正常运行且没有错误

2 个答案:

答案 0 :(得分:0)

尝试在转换上方的任意位置添加此行

enc = OneHotEncoder(handle_unknown='ignore')

然后将变换线更改为以下

enc = enc.fit(X_train)
X_train = enc.transform(X_train)
X_test = enc.transform(X_test)

答案 1 :(得分:-1)

我收到此错误

```Traceback (most recent call last):
  File "main.py", line 25, in <module>
    X_test = OneHotEncoder().transform(X_test)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/preprocessing/_encoders.py", line 726, in transform
    check_is_fitted(self, 'categories_')
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/sklearn/utils/validation.py", line 914, in check_is_fitted
    raise NotFittedError(msg % {'name': type(estimator).__name__})
sklearn.exceptions.NotFittedError: This OneHotEncoder instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.```