Question

我正在尝试为学校项目构建神经网络。我选择了一种流行的模型，该模型可确定糖尿病风险。该程序基于流行的“美洲印第安人糖尿病”数据集。我已经设置了keras和tensorflow，但是我无法让程序读取文件，它始终显示“权限被拒绝”。

我尝试将权限更新为“所有人”，但这不起作用。我很确定程序可以找到该文件，因为它们都在同一个文件夹中。也许这就是导致问题的原因？无论哪种方式，我对编程总体而言都是新手。任何帮助都将不胜感激。以下是我的代码，随附的是控制台和文件位置/内容。谢谢。

EDIT: correct picture of console and file location

from keras.models import Sequential
from keras.layers import Dense, Dropout
from sklearn.model_selection import train_test_split
import numpy

# random seed for reproducibility
numpy.random.seed(2)

# load up the data
#dataset = numpy.loadtxt("dataset.csv", delimiter=",")
dataset = open("dataset.csv")


# split into input (X) and output (Y) variables, (split the data, ouput is 0 or 1)
X = dataset[:,0:8]
Y = dataset[:,8]

# split X, Y into a train and test set
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.2, random_state=42)

# create model, add layers (specify the function)
model = Sequential()
model.add(Dense(15, input_dim=8, activation='relu')) # input layer requires input_dim param
model.add(Dense(10, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dropout(.2))
model.add(Dense(1, activation='sigmoid')) # sigmoid instead of relu for final probability between 0 and 1

# compile the model, adam gradient descent model (optimized)
model.compile(loss="binary_crossentropy", optimizer="adam", metrics=['accuracy'])

# function for fitting the data (training the network)
model.fit(x_train, y_train, epochs = 1000, batch_size=20, validation_data=(x_test, y_test))

# save it
model.save('weights.h5')

python-尝试读取csv文件时权限被拒绝

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