[英]ValueError: Found input variables with inconsistent numbers of samples: [100, 7]
[英]ValueError: Found input variables with inconsistent numbers of samples: [100, 300]
我是從 udemy 學習 KNN 的。 數據集從這里下載。
當我嘗試運行以下代碼時:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
dataset = pd.read_csv('Social_Network_Ads.csv')
x = dataset.iloc[:, [2, 3]].values
y = dataset.iloc[:, 4:].values
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.25, random_state=0)
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
x_train = sc.fit_transform(x_train)
x_test = sc.transform(x_test)
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors=5, metric='minkowski', p=2)
classifier.fit(x_train, y_train.ravel())
y_pred = classifier.predict(x_train)
from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test, y_pred)
我得到的錯誤是:
回溯(最近一次調用):文件“/home/ashutosh/Machine Learning AZ Template Folder/Part 3 - Classification/Section 15 - K-Nearest Neighbors (K-NN)/knn(1).py”,第 24 行,在厘米=混淆_矩陣(y_test,y_pred)
文件“/home/ashutosh/.local/lib/python3.7/site-packages/sklearn/metrics/_classification.py”,第268行,在confusion_matrix y_type, y_true, y_pred = _check_targets(y_true, y_pred)
文件“/home/ashutosh/.local/lib/python3.7/site-packages/sklearn/metrics/_classification.py”,第 80 行,在 _check_targets check_consistent_length(y_true, y_pred)
文件“/home/ashutosh/.local/lib/python3.7/site-packages/sklearn/utils/validation.py”,第 212 行,在 check_consistent_length “樣本:%r”% [int(l) for l in lengths ])
ValueError:發現樣本數量不一致的輸入變量:[100, 300]
換行:
y_pred = classifier.predict(x_train)
到:
y_pred = classifier.predict(x_test)
你可以走了。
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