【发布时间】:2020-02-13 10:10:29
【问题描述】:
我想知道我有什么问题我得到了错误
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,在互联网上找不到真正解决这个问题的任何东西,任何评论表示赞赏。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,我不能在这里上传,所以我在里面放了一个小 sn-p
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
另外,如果我去掉最后两行代码(预测代码),它运行良好,没有错误
【问题讨论】:
标签: python scikit-learn sklearn-pandas