Isolation Forest B04505011 工海三顧家琛.

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Presentation transcript:

Isolation Forest B04505011 工海三顧家琛

Outline Algorithm Introduction Code Review Live Demo(Using InAnalysis) ．iTree ．iForest Code Review ．Parameters ． n_estimators ． max_samples Live Demo(Using InAnalysis) Conclusion Reference

Algorithm Introduction iTree ．randomly selecting a feature ．randomly selecting a split value

Algorithm Introduction iTree Who’s abnormal?

Algorithm Introduction iForest ．measure of normality ．高度log2(n))

Code Review

WHY? Code Review n_estimators , max_samples : Default: n_estimators = 100 , max_samples = 256 WHY?

WHY? Code Review n_estimators , max_samples : Default: n_estimators = 100 , max_samples = 256 WHY?

Code Review n_estimators , max_samples : Default: n_estimators = 100 , max_samples = 256

Code Review n_estimators , max_samples : Default: n_estimators = 100 , max_samples = 256

Live demo

Conclusion

Reference https://read01.com/xD8AEnO.html http://scikit-learn.org/stable/modules/outlier_detection.html#isolation-forest http://scikit- learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html#sklear n.ensemble.IsolationForest https://read01.com/xD8AEnO.html#.WlSHaKjXZEY https://zh.wikipedia.org/wiki/AdaBoost