October 2020
Intermediate to advanced
693 pages
16h 26m
Chinese
Content preview from 机器学习实战：基于Scikit-Learn、Keras 和TensorFlow （原书第2 版）
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74
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第
2
章
不使用转换器的情况下，如果你要删除列，则可以指定字符串 "drop"。如
果你希望这些列保持不变，也可以指定 "pass through"。默认情况下，其
余列（即未列出的列）将被删除。如果你希望以不同方式处理这些列，则可以
将 remainder 这个超参数设置为任意转换器（或 "passthrough"）。
如果你使用的是 Scikit-Learn 0.19 或更早版本，则可以使用第三方库，例如 sklearn-
pandas，或者可以推出自己的自定义转换器来获得和 ColumnTransformer 相同的功
能。另外，你可以使用 FeatureUnion 类，该类可以应用于不同的转换器并合并其输
出。但是你不能为每个转换器指定不同的列，它们都适用于整个数据。你也可以使用针
对列的自定义转换器来解决这个限制（有关示例，请参见 Jupyter notebook）。
2.6 选择和训练模型
至此，你提出了问题，获得了数据，也进行了数据探索，然后对训练集和测试集进行了
抽样并编写了转换流水线，从而可以自动清理和准备机器学习算法的数据！现在是时候
选择机器学习模型并展开训练了。
2.6.1 训练和评估训练集
好消息是，在经过前面的步骤之后，事情现在变得比想象中容易很多。首先，如同我们
在第 1 章所做的，先训练一个线性回归模型：
from sklearn.linear_model import
LinearRegression
lin_reg = LinearRegression()
lin_reg.fit(housing_prepared, ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.