April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
Content preview from 精通機器學習
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第三章：分類
訓練二元分類器
我們先簡化問題
，
只嘗試辨識一個數字
，
例如
，
數字
5。
這個
「
數字
5
偵測器
」
是個
二元
分類器
，
它只能分辨兩個類別
，5
和非
5。
我們為這項分類任務建立目標向量
：
y_train_5 = (y_train == 5) #
所有的
5
都是
True，
所有其他數字都是
False
y_test_5 = (y_test == 5)
我們接著選擇一種分類器並訓練它
，
隨機梯度下降
（Stochastic Gradient Descent，SGD）
分類器是很好的起點
，
即
Scikit-Learn
的
SGDClassifier
類別
。
這個分類器的優點是
，
它可
以高效地處理非常大型的資料組
，
部分的原因是
SGD
以獨立的方式處理訓練實例
，
每次
處理一個
（
所以
SGD
非常適合用在線上學習
）。
我們來建立一個
SGDClassifier
，
並且用
整個訓練組訓練它
：
from sklearn.linear_model import
SGDClassifier
sgd_clf = SGDClassifier(random_state=42)
sgd_clf.fit(X_train, y_train_5)
SGDClassifier
的訓練過程需要依靠隨機性
（
因此名字中有
「
隨機
（stochastic）」）。
如果你想要重現結果
，
就要設定
random_state
參數
。
我們用它來偵測數字
5
的圖片
：
>>>
sgd_clf.predict([some_digit])
array([ True])
分類器猜測這張圖片代表
5（
True
）。
看起來它在這個案例猜對了 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.