ValueError：无法将Numpy阵列转换为张量（无支撑对象类型float） - 贷款状态分类

Question

我正在尝试使用混合数据类型的贷款数据集进行预处理数据

集类型：

index,Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status
0,LP001002,Male,No,0,Graduate,No,5849,0.0,NaN,360.0,1.0,Urban,Y
1,LP001003,Male,Yes,1,Graduate,No,4583,1508.0,128.0,360.0,1.0,Rural,N
2,LP001005,Male,Yes,0,Graduate,Yes,3000,0.0,66.0,360.0,1.0,Urban,Y
3,LP001006,Male,Yes,0,Not Graduate,No,2583,2358.0,120.0,360.0,1.0,Urban,Y
4,LP001008,Male,No,0,Graduate,No,6000,0.0,141.0,360.0,1.0,Urban,Y

我使用for loop将数据类型分配给每个名称：

for name, column in loan_features.items():
  dtype = column.dtype
  if dtype == object:
    dtype = tf.string
  else:
    dtype = tf.float32

  inputs[name] = tf.keras.Input(shape=(1,), name=name, dtype=dtype)

我的模型：

def loan_model(preprocessing_head, inputs):
  body = tf.keras.Sequential([
    layers.Dense(64),
    layers.Dense(1)
  ])

  preprocessed_inputs = preprocessing_head(inputs)
  result = body(preprocessed_inputs)
  model = tf.keras.Model(inputs, result)

  model.compile(loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),
                optimizer=tf.keras.optimizers.Adam())
  return model

loan_model = loan_model(loan_preprocessing, inputs)

#fit
loan_model.fit(x=loan_features_dict, y=loan_labels, epochs=10)

我遇到的错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-10-f067c1d54a2b> in <module>()
     77 
     78 #fit
---> 79 loan_model.fit(x=loan_features_dict, y=loan_labels, epochs=10)
     80 
     81 #save

1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
    100       dtype = dtypes.as_dtype(dtype).as_datatype_enum
    101   ctx.ensure_initialized()
--> 102   return ops.EagerTensor(value, ctx.device_name, dtype)
    103 
    104 

ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float).

大多数代码都遵循CSV我在TensorFlow中找到的教程。