如何解决“ValueError: y 应该是一维数组，得到了一个形状为 () 的数组。”对于极端随机森林回归器？

Question

import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import classification_report, mean_absolute_error
from sklearn import cross_validation, preprocessing
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.metrics import classification_report

# Load input data
input_file = 'traffic_data.txt'
data = []
with open(input_file, 'r') as f:
    for line in f.readlines():
        items = line[:-1].split(',')
        data.append(items)

data = np.array(data)

# Convert string data to numerical data
label_encoder = [] 
X_encoded = np.empty(data.shape)
for i, item in enumerate(data[0]):
    if item.isdigit():
        X_encoded[:, i] = data[:, i]
    else:
        label_encoder.append(preprocessing.LabelEncoder())
        X_encoded[:, i] = label_encoder[-1].fit_transform(data[:, i])

X = X_encoded[:, :-1].astype(int)
y = X_encoded[:, -1].astype(int)

# Split data into training and testing datasets 
X_train, X_test, y_train, y_test = cross_validation.train_test_split(
        X, y, test_size=0.25, random_state=5)

# Extremely Random Forests regressor
params = {'n_estimators': 100, 'max_depth': 4, 'random_state': 0}
regressor = ExtraTreesRegressor(**params)
regressor.fit(X_train, y_train)

# Compute the regressor performance on test data
y_pred = regressor.predict(X_test)
print("Mean absolute error:", round(mean_absolute_error(y_test, y_pred), 2))

# Testing encoding on single data instance
test_datapoint = ['Saturday', '10:20', 'Atlanta', 'no']
test_datapoint_encoded = [-1] * len(test_datapoint)
count = 0
for i, item in enumerate(test_datapoint):
    if item.isdigit():
        test_datapoint_encoded[i] = int(test_datapoint[i])
    else:
        test_datapoint_encoded[i] = int(label_encoder[count].transform(test_datapoint[i]))
        count = count + 1 

test_datapoint_encoded = np.array(test_datapoint_encoded)

# Predict the output for the test datapoint
print("Predicted traffic:", int(regressor.predict([test_datapoint_encoded])[0]))

** 错误似乎发生在第二个 for 循环的 else 部分，但无法找出原因：

文件“F:\Python_Workspace\AI\traffic_prediction.py”，第 114 行，在 test_datapoint_encoded[i] = int(label_encoder[count].transform(test_datapoint[i]))

文件“C:\Users\BISWADEEP\anaconda3\lib\site-packages\sklearn\preprocessing_label.py”，第 133 行，在转换中 y = column_or_1d(y, warn=True)

文件“C:\Users\BISWADEEP\anaconda3\lib\site-packages\sklearn\utils\validation.py”，第 63 行，inner_f 返回 f(*args, **kwargs)

文件“C:\Users\BISWADEEP\anaconda3\lib\site-packages\sklearn\utils\validation.py”，第 864 行，在 column_or_1d 引发 ValueError(

ValueError: y 应该是一个一维数组，得到一个形状为 () 的数组。 **

Answer 1

你能写出错误的行数是多少，并尝试检查输入数组的形状 - 看起来输入是空的。有时要预测值，您应该为模型重塑数组。： reshape_array=np.reshape(some_array,(-1,1))