Tag: anomaly-detection

ValueError: ‘c’ argument has 1000 elements, which is inconsistent with ‘x’ and ‘y’ with size 500

I’m in my way of studing anomaly detection for speech data. My original code written with LSTM, but I’m in faced to imbalance dataset. So I’m trying to have some insights from Pyod. On trying from Pyod sampling data, I just copied and pasted their code to my colab, but I encounter error as “ValueError: ‘c’ argument has 1000 elements,

Isolation Forest vs Robust Random Cut Forest in outlier detection

amazon-sagemaker anomaly-detection outliers python scikit-learn

I am examining different methods in outlier detection. I came across sklearn’s implementation of Isolation Forest and Amazon sagemaker’s implementation of RRCF (Robust Random Cut Forest). Both are ensemble methods based on decision trees, aiming to isolate every single point. The more isolation steps there are, the more likely the point is to be an inlier, and the opposite is