LibIsolationForest

Description

This project contains Rust, C++, and python implementations of the Isolation Forest algorithm. Isolation Forest is an anomaly detection algorithm based around a collection of randomly generated decision trees. For a full description of the algorithm, consult the original paper by the algorithm's creators:

https://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/icdm08b.pdf

Python Example

The python implementation can be installed via pip:

pip install IsolationForest

Here's a short code snipet that shows how to use the Python version of the library. You can also read the file test.py for a complete example. As the library matures, I'll add more test examples to this file.

from isolationforest import IsolationForest

forest = IsolationForest.Forest(num_trees, sub_sampling_size)

sample = IsolationForest.Sample("Training Sample 1")
features = []
features.append({"feature 1": feature_1_value})
# Add more features to the sample...
features.append({"feature N": feature_N_value})
sample.add_features(features)
# Add the features to the sample.
forest.add_sample(sample)
# Add more samples to the forest...

# Create the forest.
forest.create()

sample = IsolationForest.Sample("Test Sample 1")
features = []
features.append({"feature 1": feature_1_value})
# Add more features to the sample...
features.append({"feature N": feature_N_value})
# Add the features to the sample.
sample.add_features(features)

# Score the sample.
score = forest.score(sample)
normalized_score = forest.normalized_score(sample)

Rust Example

An example of how to use the Rust version of the library can be found in main.rs. As the library matures, I'll add more test examples to this file.

C++ Example

An example of how to use the C++ version of the library can be found in main.cpp. As the library matures, I'll add more test examples to this file.

Version History

1.0

• Initial version.

1.1

• Added normalized scores.
• Updated random number generation in rust, because it changed again.

License

This library is released under the MIT license, see LICENSE for details.