什么是不一致的样本数量？

Question

Ian处理机器学习问题，这是我第一次处理机器学习问题，结果显示错误。下面是我的代码

import sklearn
from sklearn import datasets
from sklearn import svm
digits = datasets.load_digits()
clf = svm.SVC(gamma=0.001,C=100)
X,Y = digits.data[:-1],digits.target[:-1]
X_mod  = X.reshape(-1,1)
Y_mod = Y.reshape(-1,1)

clf.fit(X_mod,Y_mod)
print("prediction is: ",clf.predict([-1]))

下面是它显示的错误，该怎么办

ValueError: Found input variables with inconsistent numbers of   samples: [114368, 1787]

Answer 1

如果未正确安装模型，请尝试以下代码以安装模型：

from sklearn import datasets
from sklearn import svm
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report

#Load the digits dataset 
digits = datasets.load_digits()

#Create train-test split for accuracy validation purpose 
X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target, test_size = 0.2, random_state = 0)

#Create a Support Vector Classifier placeholder
clf = svm.SVC(gamma=0.001,C=100)

#Fit the model on train data
clf.fit(X_train, y_train)

#Model score on train data
clf.score(X_train, y_train)

#Make predictions on test data
predictions = clf.predict(X_test)

#Print train, test accuracy
print('Train accuracy %s' % clf.score(X_train, y_train))
print('Test accuracy %s' % accuracy_score(predictions, y_test))

#Create confusion matrix and classification report
print(confusion_matrix(y_test, predictions))
print(classification_report(y_test, predictions))

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