NB Decision Boundary in PythonYouTube↗  IA↗(long shot)
Education  38.8K views 17 likes 2 dislikes   23 Feb 2015
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最初に、何をしようとしているかについて説明しましょう。
Okay, so let me show you where we're going with all this.
私たちはまず、supervised classificationについて、深く学ぼうとしています。
We're going to zoom ahead on supervised classification.
ここに運転のデータセットを用意しました。
So here we have the driving data set,
７５０個のデータを散布図に表示しています。
750 points now that we've drawn in our scatter plot.
目的はこの図中に、地形に基づいた分類の境界線を作ることです。
And the goal is to draw a decision boundary that will help us distinguish which
ゆっくり走るべき地形か、スピードを出せる地形か。
terrain we need to go slow on and which terrain we can go really fast.
つまりこういった感じの境界線を書けば、
So that means being able to draw a boundary that looks something like this,
２つの分類を、区分できた事になります。
where we're able to divide the two classes.
プログラムの実行イメージはこうです。
And here's what that's going to look like.
２つの分類を区別する境界線を、ここに作ることができました。
So we have our decision boundary that we can draw in here between our two
これでどのようなデータも分類できるようになります。
classes, and for any arbitrary point, we can immediately classify it as
つまり、どんな地形データでもスピードを出せるか否か、判断ができます。
terrain where we have to go slow or terrain where we can drive really fast.
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