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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