Questions tagged [isolation-forest]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
0 votes
0 answers
59 views

Evaluate multiple Isolation Forest estimators during GridSearchCV with custom scorer function

I have a sample of values that don't have a y target value. Actually, the X features (predictors) are all used to fit the Isolation Forest estimator. The goal is to identify which of those X-features ...
user avatar
  • 101
0 votes
0 answers
28 views

Anomaly detection and root cause analysis

ARIMA is widely used for anomaly detection on time-series data e.g. stock price prediction. ARIMA assumes that future value of a variable (stock price in our case) is dependent on its previous values. ...
user avatar
0 votes
0 answers
11 views

Can I run isolation forest on existing data to find anomalies, save it for the future and use it on incoming data?

One of the major arguments I had recently is if we can save an unsupervised learning model to disk and use it later on incoming data. Isolation forest is one of the models that I use a lot for ...
user avatar
0 votes
1 answer
44 views

Word2vec to encode medical procedures when using isolation forests

I am planning to use Isolation Forests in R (solitude package) to identify outlier medical claims in my data. Each row of my data represents the group of drugs that each provider has administered in ...
user avatar
  • 241
0 votes
0 answers
106 views

Isolation Forest in R using Solitude - From the results how can I identify the anomalous records

I am trying to use the Isolation Forest algorithm in the Solitude package to identify anomalous rows in my data. I'm using the examples in the documentation to learn about the algorithm, this example ...
user avatar
  • 241
1 vote
2 answers
61 views

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 ...
user avatar
  • 1,851
0 votes
2 answers
362 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 ...
user avatar
0 votes
0 answers
58 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 ...
user avatar
0 votes
1 answer
104 views

Calculating accuracy score of isolation forest model returning error

My code is as follows: ...
user avatar
  • 1
0 votes
0 answers
102 views

ValueError: Number of features of the model must match the input. Model n_features is 1 and input n_features is 2. Isolation Forest Method

...
user avatar
  • 101
2 votes
1 answer
296 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 ...
user avatar
  • 123
0 votes
2 answers
68 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 ...
user avatar
2 votes
1 answer
88 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 ...
user avatar
2 votes
1 answer
117 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 ...
user avatar
2 votes
0 answers
373 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(). ...
user avatar
  • 389
4 votes
1 answer
91 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 ...
user avatar
0 votes
2 answers
72 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: ...
user avatar
  • 111
0 votes
2 answers
575 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 ...
user avatar
0 votes
0 answers
171 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, ...
user avatar
1 vote
2 answers
83 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 ...
user avatar
4 votes
0 answers
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 ...
user avatar
1 vote
1 answer
140 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 ...
user avatar