深度学习：Python使用Keras神经网络进行简单文本分类

2020-02-2309:20:27人工智能与大数据Comments3,188 views字数 3670阅读模式

使用Keras进行文本分类。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

准备数据集

出于演示目的，我们将使用 20个新闻组数据集。数据分为20个类别，我们的工作是预测这些类别。如下所示：文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

通常，对于深度学习，我们将训练和测试数据分开。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

导入所需的软件包

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

import pandas as pd文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

import numpy as np文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

import pickle文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

from keras.preprocessing.text import Tokenizer文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

from keras.models import Sequential文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

from keras.layers import Activation, Dense, Dropout文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

from sklearn.preprocessing import LabelBinarizer文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

import sklearn.datasets as skds文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

from pathlib import Path

将数据从文件加载到Python变量

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

10文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

11文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

12文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

13文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

14文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

15文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

16文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

17文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

18文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

19文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

20文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

21文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

22文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# For reproducibility文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

np.random.seed(1237)文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

label_index = files_train.target文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

label_names = files_train.target_names文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

labelled_files = files_train.filenames文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

data_tags = ["filename","category","news"]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

data_list = []文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# Read and add data from file to a list文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

data = pd.DataFrame.from_records(data_list, columns=data_tags)

在我们的情况下，数据无法以CSV格式提供。我们有文本数据文件，文件存放的目录是我们的标签或类别。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

我们将使用scikit-learn load_files方法。这种方法可以为我们提供原始数据以及标签和标签索引。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

在以上代码的结尾，我们将有一个数据框，其中包含文件名，类别和实际数据。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

拆分数据进行训练和测试

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# lets take 80% data as training and remaining 20% for test.文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

train_size = int(len(data) * .8)文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

train_posts = data['news'][:train_size]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

train_tags = data['category'][:train_size]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

train_files_names = data['filename'][:train_size]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

test_posts = data['news'][train_size:]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

test_tags = data['category'][train_size:]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

test_files_names = data['filename'][train_size:]

标记化并准备词汇

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

10文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

11文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

12文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

13文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

14文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

15文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# 20 news groups文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

num_labels = 20文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

vocab_size = 15000文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

batch_size = 100文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# define Tokenizer with Vocab Size文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

tokenizer = Tokenizer(num_words=vocab_size)文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

tokenizer.fit_on_texts(train_posts)

在对文本进行分类时，我们首先使用Bag Of Words方法对文本进行预处理。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

预处理输出标签/类

在将文本转换为数字向量后，我们还需要确保标签以神经网络模型接受的数字格式表示。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

建立Keras模型并拟合

PowerShell文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

10文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

11文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

12文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

13文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

14文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

15文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

16文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

17文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

18文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

19文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

model = Sequential()

它为输入数据的形状以及构成模型的图层类型提供了简单的配置。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

这是一些适合度和测试准确性的代码段文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

10文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

11文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

100/8145 [..............................] - ETA: 31s - loss: 1.0746e-04 - acc: 1.0000文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

200/8145 [..............................] - ETA: 31s - loss: 0.0186 - acc: 0.9950文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

300/8145 [>.............................] - ETA: 35s - loss: 0.0125 - acc: 0.9967文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

400/8145 [>.............................] - ETA: 32s - loss: 0.0094 - acc: 0.9975文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

500/8145 [>.............................] - ETA: 30s - loss: 0.0153 - acc: 0.9960文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

...文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7900/8145 [============================>.] - ETA: 0s - loss: 0.1256 - acc: 0.9854文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8000/8145 [============================>.] - ETA: 0s - loss: 0.1261 - acc: 0.9855文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8100/8145 [============================>.] - ETA: 0s - loss: 0.1285 - acc: 0.9854文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8145/8145 [==============================] - 29s 4ms/step - loss: 0.1293 - acc: 0.9854 - val_loss: 1.0597 - val_acc: 0.8742文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

Test accuracy:

评估模型

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

10文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

11文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

12文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

for i in range(10):文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

prediction = model.predict(np.array([x_test[i]]))文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

predicted_label = text_labels[np.argmax(prediction[0])]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

print(test_files_names.iloc[i])文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

print('Actual label:' + test_tags.iloc[i])文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

print("Predicted label: " + predicted_label)

在Fit方法训练了我们的数据集之后，我们将如上所述评估模型。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

混淆矩阵

混淆矩阵是可视化模型准确性的最佳方法之一。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

保存模型文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

通常，深度学习的用例就像在不同的会话中进行数据训练，而使用训练后的模型进行预测一样。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# creates a HDF5 file ''文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

model.model.save('')文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

# Save Tokenizer i.e. Vocabulary文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

with open('', 'wb') as handle:文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

pickle.dump(tokenizer, handle, protocol=pickle.HIGHEST_PROTOCOL)

Keras没有任何实用程序方法可将Tokenizer与模型一起保存。我们必须单独序列化它。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

加载Keras模型

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

预测环境还需要注意标签。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1	encoder.classes_ #LabelBinarizer

预测

如前所述，我们已经预留了一些文件进行实际测试。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

Python文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

3文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

4文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

5文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

6文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

7文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

8文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

9文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

10文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

11文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

12文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

13文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

14文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

15文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

16文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

17文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

18文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

19文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

20文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

21文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

22文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

23文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

24文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

25文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

26文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

27文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

labels = np.array(['', '', '',文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

'', '', '',文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

'', '', '', '',文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

'', '', '', '', '',文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

'', '', '',文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

'', ''])文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

...文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

for x_t in x_tokenized:文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

prediction = model.predict(np.array([x_t]))文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

predicted_label = labels[np.argmax(prediction[0])]文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

print("File ->", test_files[i], "Predicted label: " + predicted_label)文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

i += 1

输出量

1文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

2文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

File -> C:\DL\20news-bydate\20news-bydate-test\\38758 Predicted label:文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

File -> C:\DL\20news-bydate\20news-bydate-test\\76115 Predicted label:文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

File -> C:\DL\20news-bydate\20news-bydate-test\\21329 Predicted label:

我们知道目录名是文件的真实标签，因此上述预测是准确的。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

结论

在本文中，我们使用Keras python库构建了一个简单而强大的神经网络。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/ai/17862.html

深度学习：Python使用Keras神经网络进行简单文本分类

准备数据集

导入所需的软件包

将数据从文件加载到Python变量

拆分数据进行训练和测试

标记化并准备词汇

预处理输出标签/类

建立Keras模型并拟合

评估模型

混淆矩阵

加载Keras模型

预测

输出量

结论

ControlNet再升级！字节提出ControlNet ++！

Suno AI创作音乐的专业级保姆教程

英伟达黄仁勋：为什么还要用Python？命令行都不需要！GPU开发时代将至!

「现实版贾维斯」RPA+AI技术如何革新你的工作？

5个AIGC导航网站，建议收藏！

GPT-4.5 Turbo疑似提前曝光，OpenAI要发布了？

Claude 官方提示词模板之中文版（含API Prompt）

Claude 3是什么鬼东西？能超越GPT4

AI无监督学习“聚类算法”详解，理论实现到案例说明

字节扣子Coze深度教学：免费使用 GPT-4 Turbo，GPTs，DALLE 3，支持多agent协同

Comment