Questions tagged [isolation-forest]

Question 1

I am using sklearn's Isolation Forest as a model to detect anomalies. My dataset is relatively small, 50 records with only 2-3 features. To prevent any overfitting, what would you recommend to tune ...

Question 2

I am using sklearn's IsolationForest for unsupervised anomaly detection task. According to the docs, https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html, there are ...

Question 3

I am looking to better understand sklearn IsolationForest decision_function. My understanding is that if the metric is closer to -1 then the model is more confident ...

Question 4

I have implemented an Isolation Forest algorithm for anomaly detection (unsupervised learning), where I divided my dataset into 1000 subsets, and for each subset, there is one isolation tree. This ...

Question 5

I'm performing some outlier detection and am plotting an IsolationForest with varying levels of contamination against PCA variance reduction. I want to maximize the outlier count while minimizing loss ...

Question 6

In unsupervised anomaly detection, does including the contamination percentage turn isolation forest into supervised instead of unsupervised when I fit the data after?

Question 7

I have recently came across on this algorithm and was working on my graduation project. As per my understanding, we creates sub trees for each sub samples. Then we calculates the scores for each ...

Question 8

When using Isolation Forest for outlier detection (an unsupervised case), how to evaluate the performance of isolation forest?

Question 9

I am trying to do unsupervised anomaly detection on a dataset with a dozen of variables. None of them have descriptions, and the dataset doesn't have any labels or class variable. I have tried using a ...

Question 10

Let say, I have the anomaly detection (unsupervised learning) dataset with 10 observations (two features). The datasets is like below: After executing the model, following are the results (anomalies ...

Question 11

[I am a total beginner in machine learning algorithms] I have 10 spectrograms (lines) for phytoplankton (each composed of 288 points). Each spectrogram is associated with a phytoplankton dendity data ...

Question 12

I have a dataset which has a column of prices, a column of dates, and various other columns of numerical and categorical values. I would like to find outlier prices based on all the columns in the ...

Question 13

im trying to build an outlier detector to find outliers in test data. That data varies a bit (more test channels, longer/shorter testing). First im applying the train test split because i want to use ...

Question 14

I'm trying to build an anomaly detection model using Isolation Forest. I currently have 12 features, about half of them depends on the presence of a particular data field, say ...

Question 15

I'm running sklearn's IsolationForest on a dataset containing 2 classes of data, one that I know is the anomaly (~1.5% of the entire dataset), the other is the normal dataset. I'm using this (shuffled)...

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Questions tagged [isolation-forest]

Isolation Forest sample size

Unsupervised Isolation Forrest sklearn hyperparameters

Confirm understanding of decision_function in Isolation Forest sklearn

Determine best hyperprameteres in GridSearch - Isolation Forest

PCA Variance Reduction local outlier minima

Does Including Contamination Turn Isolation Forest into Supervised?

Loss function in Isolation Forest

Evaluating isolation forest (Unsupervised learning use case)

Doing unsupervised anomaly detection on a dataset without any labels and without variable descriptions

Confused with Isolation Forest

Varying feature vector lengths for learning

How to apply a tree-based model with numerical and categorical values to find outliers

Can GridSearchCV be used for unsupervised learning?

Handling features dependent on a data field that may not be present in sample

Understanding Isolation Forest predictions

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