rewrite the code using sparse caterorical crossentropy

Keras 提供了一个名为 `sparse_categorical_crossentropy` 的损失函数，它可以用来替换 `categorical_crossentropy`。

例如，如果你当前正在使用 `categorical_crossentropy`，你可以将它替换为 `sparse_categorical_crossentropy`:

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])

更改为:

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

需要注意的是，在使用 `sparse_categorical_crossentropy` 时，标签需要是整数类型，而不是 one-hot 编码。

相关问题

rewrite your code above to use Pipeline

Sure! Here's the rewritten code using `Pipeline` from scikit-learn:

from sklearn.pipeline import Pipeline
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler

# Define the features and target variable
features = ['INDUS', 'CRIM']
target = 'target'

# Create the pipeline
pipeline = Pipeline([
    ('scaler', StandardScaler()),
    ('regressor', LinearRegression())
])

# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(bos[features], bos[target], test_size=0.2, random_state=0)

# Fit the pipeline on the training data
pipeline.fit(X_train, y_train)

# Evaluate the model on the training and testing data
train_accuracy = pipeline.score(X_train, y_train)
test_accuracy = pipeline.score(X_test, y_test)

print("Training accuracy:", train_accuracy)
print("Testing accuracy:", test_accuracy)

In this code, we create a `Pipeline` object consisting of two steps: a `StandardScaler` for feature scaling and a `LinearRegression` model. The `ColumnTransformer` is not required here since we only have numerical features.

We then split the data into training and testing sets using `train_test_split`. Next, we fit the pipeline on the training data and evaluate the model's accuracy on both the training and testing data using the `score` method. Finally, we print the training and testing accuracies.

the HTTP rewrite module requires the PCRE library

HTTP rewrite模块需要PCRE库的支持。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *3* [./configure: error: the HTTP rewrite module requires the PCRE library.](https://blog.csdn.net/weixin_35755188/article/details/129081018)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
- *2* [the HTTP rewrite module requires the PCRE libraryh解决方法](https://blog.csdn.net/lzc4869/article/details/75976007)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
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