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input { file { path => "/var/log/*.log" } } output { elasticsearch { hosts => ["localhost:9200"] index => "logstash-%{+YYYY.MM.dd}" } }
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import pandas as pd from sklearn.ensemble import IsolationForest # ¼ÓÔØÈÕÖ¾Êý¾Ý data = pd.read_csv("logs.csv") # ÌáÈ¡ÌØÕ÷ features = data.drop(["label", "timestamp"], axis=1) # ʹÓÃÁæØêÉÁÖËã·¨¾ÙÐÐÍþв¼ì²â model = IsolationForest(contamination=0.1) model.fit(features) # Õ¹ÍûÒì³£Ñù±¾ predictions = model.predict(features) # Êä³öÒì³£Ñù±¾ outliers = data[predictions == -1] print(outliers)
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Elastic. Logstash – Collect, Parse, and Enrich Data. https://www.elastic.co/logstash.
Elastic. Elasticsearch – Fast, Distributed, and Highly Available Search Engine. https://www.elastic.co/elasticsearch.
Elastic. Kibana – Explore & Visualize Your Data. https://www.elastic.co/kibana.
Scikit-learn. Isolation Forest. https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html.
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