Questions tagged [novelty-detection]

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7 questions with no upvoted or accepted answers
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1answer
130 views

Detecting changes in large number of time-series that share seasonality

I have large number of time-series that are independent of each other, but share some seasonality patterns. I need to detect anomalies/changes (increased volume, change in mean), that appear in the ...
2
votes
1answer
4k views

Best way to train one-class SVM

Let`s say I have training data which contains 10 classes and have build a classifier using this data. When applying this classifier in real life it may encounter examples not belong to the classes ...
1
vote
2answers
132 views

How to choose a method for binary classifier based on only positive and unlabelled examples?

I need to build a binary classifier with machine learning, as I fail to manually choose a combination of features to achieve minimal fraction of false positives. What is best practice for choosing a ...
1
vote
0answers
57 views

Weighting loss function using Voronoi-tessellation of response space

Let's say you have some Real-valued features $\mathbf{X}$ and Real-valued univariate responses $\mathbf{y}$. We want to fit a regression model to this data: $$\mathbf{y} = f\left(\mathbf{X};\beta\...
0
votes
0answers
62 views

LocalOutlierFactor scikit-learn

My goal is to use the LocalOutlierFactor class from scikit-learn to do real-time Novelty Detection. This can be achieved by setting novelty=True in the constructor, ...
0
votes
0answers
50 views

Are Novelty Effects accounted for in Power Analysis?

I'm a bit a new hypothesis testing, so I hope that this question makes sense. Say that I proposed a new treatment (like a new drug or something) and I wanted to test whether this drug was effective or ...
0
votes
0answers
732 views

Novelty and Outlier Detection in Unsupervised Learning Style

Currently I am looking for some method to do novelty and outlier detection. I found some good example here using scikit-learn (Link1). However, it is based on supervised learning and I believe the ...