scikit_learn中的fit(),fit_transform()和transform()有什么区别? [英] what is the difference between fit() ,fit_transform() and transform() in scikit_learn?
问题描述
这是用于特征缩放的代码,其中我正在使用 fit_transform()
和 transform()
:
This is code for feature scaling in which i am using fit_transform()
and transform()
:
##Feature scaling
from sklearn.preprocessing import StandardScaler
sc_x=StandardScaler()
X_train=sc_x.fit_transform(X_train)
X_test=sc_x.transform(X_test)
推荐答案
fit
意味着使模型适合所提供的数据.这是模型从数据中学习"的地方.
fit
means to fit the model to the data being provided. This is where the model "learns" from the data.
transform
意味着根据拟合的模型转换数据(产生模型输出).
transform
means to transform the data (produce model outputs) according to the fitted model.
fit_transform
意味着同时进行-将模型拟合到数据,然后根据拟合的模型转换数据.调用 fit_transform
是一种便利,可以避免在同一输入上依次调用 fit
和 transform
.
fit_transform
means to do both - Fit the model to the data, then transform the data according to the fitted model. Calling fit_transform
is a convenience to avoid needing to call fit
and transform
sequentially on the same input.
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