問題：なぜ機械学習の実験結果が再現できないのか
「先週良い結果が出たモデルがあったんだけど、どのパラメータを使ったか覚えてる？」
機械学習プロジェクトでこんな会話を聞いたことはありませんか？多くのチームが直面する典型的な問題です。
[Read More]On the use of distributed representations bagging for class classification and generalization performance
After the distributed representation has been obtained, the After the distributed representation is obtained, machine learning can be used to classify it.
Models that can be used include
- Decision Tree
- SVM Support Vector Machine
- NN Neural Networks
and others.
SVM is included in NN in a broad sense.
In this section, we will use the decision tree method.
Bagging
- Image of majority voting with multiple decision trees
- Simple theory
- Decision trees are highly explainable and are a classic machine learning model.
- Computational load is light compared to deep learning
- Depends on the size of the model
- Not much explainability
- Do we want to analyze each of the multiple decision trees?
``py from sklearn.ensemble import BaggingClassifier from sklearn.tree import DecisionTreeClassifier
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