Questions tagged [isolation-forest]

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How do I determine the top "reason" for anomaly when using Isolation Forests

I am using Isolation Forests for Anomaly Detection. Say, my set has 10 variables, var1, var2, ..., var10, and I found an anomaly. Can I rank the 10 variables var1, var2, ..., var10 in such a way I can ...
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1answer
59 views

Anomaly (Outlier) Detection with Isolation Forest too sensitive even with low contamination

I'm trying to use the sklearn implementation of the Isolation Forest algorithm to detect anomalies in my time series data. However, even with a very low contamination parameter (0.0001), it is ...
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0answers
11 views

outlier detection: zscore vs isolation forest

Trying to understand when to use zscore and when to use isolation forest for determining outliers in the data. I know that zscore is only applicable if data is normally distributed whereas ...
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1answer
16 views
2
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1answer
119 views

The affect of bootstrap on Isolation Forest

I've been using isolation forest for anomaly detection, and reviewing its parameters at scikit-learn (link). Looking at "bootstrap", I'm not quite clear what using bootstrap would cause. For ...
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1answer
54 views

Anomaly Detection

I have a problem where I want to identify Vendors with unusual high amount invoices. What would be the best way to identify such invoices? I am trying to use Isolation Forest but having trouble in ...
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0answers
57 views

Cross-Validation for Unsupervised Anomaly Detection with Isolation Forest

I am wondering whether I can perform any kind of Cross-Validation or GridSearchCV for unsupervised learning. The thing is that I have the ground truth labels (but since it is unsupervised I just drop ...
1
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1answer
59 views

Geolocation Based Anomaly Detection in IPs Using Isolation Forest

I'm trying to detect anomalies based on geolocation from IP addresses on a server access log file. I have created two features country and geo_velocity, using the IP address and the timestamp of each ...
2
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0answers
198 views

How SHAP value explains contribution of features for outliers event?

I'm trying to understand and experiment with how the SHAP value can explain behaviour for each outlier events (rows) and how it can be related to shap.force_plot(). ...
4
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1answer
75 views

Why do Isolation Forest implementations turn it into a supervised learning problem (with random values for the target?)

I am looking at various implementations of the Isolation Forest in python and R. Both sklearn in python and solitude in R use a y variable with the ExtraTrees regressor. Since, Isolation Forest is ...
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1answer
49 views

Incorrect multi-variate anomaly detection - Isolation Forest Python

My data looks like below. it has 333 rows and 2 columns. Clearly the first row is anomaly. ndf: ...
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2answers
350 views

Cross-Validation in Anomaly Detection with Labelled Data

I am working on a project where I train anomaly detection algorithms Isolation Forest and Auto-Encoder. My data is labelled so I have the ground truth but the nature of the problem requires ...
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0answers
120 views

Anomaly Detection over multivariate data containing Nominal and numerical predictors

I am trying to implement Anomaly Detection over a multivariate dataset having nominal and numerical predictors. Dataset has following pattern: If we consider the below sample records, category_id, ...
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2answers
57 views

Identify the parameter causing the anomaly in a multivariate dataset

I have a payment transaction dataset with a large number of predictor variables. I am trying to build a model for anomaly detection and I have evaluated various algorithms/approaches for the same like ...
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0answers
1k views

Dealing with categorical variables in Isolation Forest

Isolation Forest is widely used when dealing with outlier/anomaly detection when we have no labels. The theory behind is that making random split at random points and counting how many splits you do ...
1
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1answer
123 views

Isolation Forest: simple example

Can some one please explain Isolation Forests more clearly? Everywhere I search, I find the same explanation: Isolation Forest ‘isolates’ observations by randomly selecting a feature and then ...