Questions tagged [isolation-forest]

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How to detect anomalies in multiple different IP addresses?

Given that my input data consists of various destination IP addresses and its incoming connections from source IP addresses with country codes during certain timestamps, I would like to detect ...
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77 views

Feature engineering for fraud detection with Isolation Forest

I am researching and doing a project related to the detection of fraudulent transactions in the financial system. For this research we are working with unsupervised learning, more precisely we are ...
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10 views

How can I generate a plot of the partitions in Isolation Forests

I have seen this plot is used to indicated how anomalies are isolated via partitioning in Isolation Forests. Is there a library to automatically plot this from a dataset? The plot I want to generate ...
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123 views

How can we introduce an anomaly class as a positive class to sklearn IsolationForest?

I inspired by this notebook, and I'm experimenting IsolationForest (IF) algorithm using scikit-learn==0.22.2.post1 for anomaly ...
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1answer
110 views

incorrect results of IsolationForest

I inspired by this notebook, and I'm experimenting IsolationForest algorithm for anomaly detection context on the SF version of KDDCUP99 dataset, including 4 ...
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35 views

Anomaly detection methods assessed with AUC (poor performance unbalanced data)

I have a data with 10 000 rows and 20 columns. I also have a variable indicating if the row is an anomaly (1) or if it is a "normal data" (0). In my data there are 5% anomalies. The purpose ...
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1answer
71 views

Why is One Class SVM predicting that half my dataset consists of outliers?

I am currently working on a dataset with 14 continuous features, a categorical target over five classes, and 90,000 samples. My current goal is to explore outliers in the dataset, and to that end I ...
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863 views

How to Tune Isolation Forest?

Many online blogs talk about using Isolation Forest for anomaly detection. But I got a very poor result. The data used is house prices data from Kaggle. I used IForest and KNN from pyod to identify 1% ...
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49 views

Anomaly/Outlier Detection for Arbitrary Shaped Data?

The following plots use the data from Kaggle's House Prices competition. SalePrice is the target variable. I want to find a method to identify outliers (as shown in red in plot 3 & 4) ...
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29 views

isolation forest erratic behaviour

I have gotten a dataset that has continuous values which are normalized in the range from 0 to 1, is it approximately 200 records with 14 features, and like 30 percent of the data present there are ...
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42 views

Evaluation method for outlier detection with a data that has no labels

I am applying an unsupervised outlier detection model called isolation-Forest to detect outliers using unlabelled time-series data. I do not have labels that distinguish a true outlier from a false ...
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1answer
1k views

Anomaly Detection over multivariate categorical and numerical predictors

I am trying to implement Anomaly Detection over a multivariate dataset having categorical and numerical predictors. If we consider the below sample records, product_type, company_type and currency are ...
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78 views

Can you use the isolation forest algorithm on large sample sizes?

The original isolation forest paper states that the algorithm works best on small subsamples, but is it okay to use it on large sample sizes or are other anomaly detection algorithms better?
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158 views

Can you use the isolation forest algorithm on a large sample size?

I've been using the scikit learn sklearn.ensemble.IsolationForest implementation of the isolation forest to detect anomalies in my datasets that range from 100s of ...
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27 views

Separating anomalys using Isolation Forest, Is my approach correct?

I am a fairly new guy to ML and I am having some trouble choosing a algorithm to the job for me. My data set consists physical measurements where part of the samples were contaminated. In this case, ...
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40 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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1answer
154 views

Meaning Of The Terms In Isolation Forest Anomaly Scoring

In an isolation forest the anomaly score of a point is given by: $$2^{\frac{-E(h(x))}{c(m)}}$$ Now supposedly c(m) is the average length to termination in the search tree. And, E(h(x)) is the ...
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62 views

Discordance between various methods of multivariate outliers detection

Here is a small "toy example" dataset, with 15 individuals described by 6 variables (this is R language): ...
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122 views

Oversampling/Undersampling in respect to Train and Test - Isolation Forest

I've got a quite imbalanced data set. 144.496 : 162 -> ratio of 1000:1 I would like to use IsolationForest to detect the 162 anomalys. I've already split the data. However, the iForest doesn't ...
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1answer
1k views

Isolation forest with categorical data?

I understand how isolation forests can work with numeric data, but I wonder how it can work with categorical data? Also, at least when working with Sci-kit-Learn, the recommendation I saw was to ...