Title | Link |
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Decision tree analysis | LINK |
Decision tree and random forest | LINK |
How to Handle Imbalanced Classes in Machine Learning(Pre-data processing) | LINK |
scikit-learn
Title | Link |
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RandomForestClassifier parameters | LINK |
GridSearchCV | LINK |
make_classification(Data generation function) | LINK |
.predict_proba(Show the probability of being classified in class) | LINK |
feature_importances_(Evaluate the importance of features in a random forest) | LINK |
KERAS
Title | Link |
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mnist.load_data()MNIST (Handwritten digit database) | LINK |
to_categorical(Example:0->[0,0,0],1->[0,1,0],2->[0,0,1]Conversion to) | LINK |
Sequential model | LINK |
Title | Link |
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Cross-validation(cross validation) | LINK |
Hyperparameters | LINK |
ROC,ACU | LINK |
Feature value | LINK |
Title | Link |
---|---|
scikit-Generate a confusion matrix with learn and calculate the precision rate, recall rate, F1 value, etc. | LINK |
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