我正在研究涉及两个类的分类问题。我需要在数据集上训练模型,并在将一个值作为每个属性的输入后预测正确的类别。这是数据集的片段。这些类是 0
和 1
。
这是我用来训练和测试模型的代码:
X = df.drop(["classification"], axis=1)
y = df["classification"]
x_scaler = MinMaxScaler()
x_scaler.fit(X)
column_names = X.columns
X[column_names] = x_scaler.transform(X)
X_train, X_test, y_train, y_test = train_test_split(
X, y, test_size= 0.2, shuffle=True)
我尝试从用户那里获取输入,如下所示:
userInput=input("Enter 14 attributes separated by commas")
#userInput=userInput.split(",")
#userInput=[np.float32(c) for c in userInput]
并预测:
pred=model.predict(userInput)
但我收到错误:
AttributeError: 'str' object has no attribute 'ndim'
我还尝试手动输入属性:
prediction=np.array([40,8,1,2,0,2,6,10,34,40,16,23,67,25])
print(prediction.shape) # Shape is (14,)
print(prediction[0].shape) # Shape is ()
print(prediction[0:1].shape) #Shape is (1,)
print(X_test[0:1].shape) #Shape is (1, 14)
并通过以下方式进行预测:
(1) pred = model.predict(x=np.array(prediction[0:1].shape))
(2) pred = model.predict(x=np.array(prediction[0].shape))
(3) pred = model.predict(prediction)
(4) pred = model.predict([40,8,1,2,0,2,6,10,34,40,16,23,67,25])
(5) pred = model.predict(prediction.shape)
(6) pred = model.predict([40],[8],[1],[2],[0],[2],[6],[10],[34],[40],[16],[23],[67],[25])
但是在 1
到 4
的情况下我收到此错误
ValueError: Error when checking input: expected dense_1_input to have shape (14,) but got array with shape (1,)
这分别是 5
和 6
的情况
AttributeError: 'tuple' object has no attribute 'ndim'
TypeError: predict() takes from 2 to 9 positional arguments but 15 were given
另外,我尝试运行这个'并且它有效:
pred=model.predict(X_test)
但预测却并非如此。我尝试过:
(1) print(np.argmax(pred(userInput)))
(2) print(np.argmax(pred(prediction)))
使用 .shape
也不起作用,并给出错误:
TypeError: 'list' object is not callable
训练数据的形状:(320, 14) 测试数据形状:(80, 14)
有什么方法可以获取用户的输入并将其用于预测吗?
最佳答案
当你预测时
pred=model.predict(userInput)
您收到错误 AttributeError: 'str' object has no attribute 'ndim'
因为您将字符串传递给函数。您必须拆分从终端读取的字符串并将字符串转换为整数。
inputString = "1, 2, 3,4"
sample = inputString.replace(" ", "").split(",")
sample = [int(x) for x in sample]
print(sample)
[1, 2, 3, 4]
对于预测,请尝试将样本传递给预测方法,如下所示:
pred = model.predict([[40,8,1,2,0,2,6,10,34,40,16,23,67,25]])
关于python - TensorFlow 机器学习 - 对用户输入进行预测,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/59827963/