ValueError: Number of features of the model must match the input. Model n_features is 464 and input n_features is 2

Question

我正在尝试预测香水的成本，但在“answer = (clf.predict(result))”行中出现错误

cursor.execute('SELECT * FROM info')
    info = cursor.fetchall()
    for line in info:
        z.append(line[0:2])
        y.append(line[2])

    enc.fit(z)
    x = enc.transform(z).toarray()

    result = []
    clf = tree.DecisionTreeClassifier()
    clf = clf.fit(x, y)
    new = input('enter the Model, Volume of your perfume to see the cost: example = Midnighto,50 ').split(',')
    enc.fit([new])
    result = enc.transform([new]).toarray()

    answer = (clf.predict(result))
    print(answer)

Answer 1

您不必再次用新输入拟合 enc，只需使用适合 X 的函数进行变换（您所做的是 OneHotEncoding 新样本，仅考虑该特征的一个可能值，您必须考虑 X 数据中所有可能的特征类别)。所以删除下一行：

enc.fit([new])

之后，请检查 X 和结果是否具有相同数量的特征。您可以使用函数 shape.

此外，我建议您使用训练和测试数据来查看您的模型是否过拟合。然后，您可以应用您的个人预测。

ValueError: Number of features of the model must match the input. Model n_features is 464 and input n_features is 2

ValueError: Number of features of the model must match the input. Model n_features is 464 and input n_features is 2

transform

decision-tree

python-3.x

scikit-learn

one-hot-encoding