我是TensorFlow / Machine Learning的新手，因此遇到了一些困难。我有CSV格式的数据集在这里，想与熊猫们喜欢读它这里。它在不同的数据集上工作，但我进行了修改和扩展，但我认为这里缺少重要的内容。基本上，我要做的所有工作都是根据给定的数据集预测“总体”评分。这是我的代码和得到的追溯：
import pandas as pd
import tensorflow as tf
import tempfile
COLUMNS = ["reviewerID", "asin", "reviewerName", "helpful_0", "helpful_1", "reviewText",
"overall", "summary", "unixReviewTime"]
CATEGORICAL_COLUMNS = ["reviewerID", "reviewerName", "reviewText", "summary"]
CONTINUOUS_COLUMNS = ["helpful_0", "helpful_1", "unixReviewTime"]
df_train = pd.read_csv('Digital_Music_5.csv', names=COLUMNS, skipinitialspace=True,
low_memory=False, skiprows=1)
df_test = pd.read_csv('Digital_Music_5_test.csv', names=COLUMNS,
skipinitialspace=True, skiprows=1)
LABEL_COLUMN = "label"
df_train[LABEL_COLUMN] = df_train["overall"]
df_test[LABEL_COLUMN] = df_train["overall"]
print(df_train)
def input_fn(df):
# Creates a dictionary mapping from each continuous feature column name (k)
# to the …