Questions tagged [anomaly]
23 questions
24
votes
4 answers
Looking for a good package for anomaly detection in time series
Is there a comprehensive open source package (preferably in python or R) that can be used for anomaly detection in time series?
There is a one class SVM package in scikit-learn but it is not for the time series data. I’m looking for more…
pythinker
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2 answers
Anomaly detection without any knowledge about structure
I have an interesting question, my code needs to be able to handle structured data where I don't know much about the structure at development time. I know the samples follow a schema that can be nested and the leafs contain some basic primitives…
Jan van der Vegt
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1 answer
How to test unsupervised learning methods for anomaly detection?
How to test unsupervised learning methods for anomaly detection?
I am looking for a test strategy to evaluate my result of my anomaly detection technique?
what is your offer more than evaluate with different algorithms.
My data is some time series…
user10296606
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1 answer
How to determine the abnormality of a specific variable by taking into account all the other variables in the data?
I have an issue of machine learning/anomaly detection. Indeed, I have a variable Y and several other variables X. The purpose is to quantify the degree of abnormality of the data on Y but I have to take into account the values on the other variables…
AdrienC
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2 answers
How to perform Anomaly Detection on a force profile?
I have a set of force profiles of an industrial machine. I'm trying to develop an algorithm that tries to understand when a new profile is "anomalous" with respect to the ones in "normal operating conditions".
In the picture below you can see the…
Xela95
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1 answer
How to improve precision under imbalanced classification
I am using an imbalanced dataset (rare positive cases) to learn models for prediction and the final good AUC is 0.92 but the F1 score is very low0.2.
Is it possible to add some key features which will change the class probabilistic distribution and…
LUSAQX
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Practical problems in anomaly detection where the number of normal data is extremely high compared to abnormal data
If the ratio of abnormal data is about 1 to 10,000 normal data, even if the true negative rate is 99%, there will be 100 false positive data, and the precision( TP/(TP+FP) ) will be low.
If this kind of anomaly detection is to be put to practical…
pie
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Anomaly Detection System
I need a sanity check. I want to create an anomaly detection system.
The logic which I am planning to use is the following:
Find anomalies in the past using Seasonal Hybrid Extreme Studentized Deviate Test.
Binarise the anomalies (1 the…
Angelos
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vote
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How to find anomalies/outliers in Panel Data?
I have panel data based on 900000 different entities with 384 time steps and the data is not normally distributed. I am looking for outliers/anomalies, this is unsupervised as I have no examples of anomalies/outliers.
Apart from clustering methods…
Kale-ab Tessera
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4 answers
How to detect anomalous points
As is clear from the figure, the blue points, which don't follow the trend, are anomalous points.
I'm wondering about the best non-parametric method to detect those points. I have tested some outlier detection methods such as standard deviation,…
Arkan
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How to detect anomalies in each feature - time series
I have a dataset with 5 features corresponding to 5 sensors that measure each three seconds the state of an accelerator. It is structured as well:
Sensor 1 | Sensor 2 | Sensor 3 | Sensor 4 | Sensor 5 | Label
1.5 1.1 0.8 1.2 …
Fabio
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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 say that I have an anomaly and the main reason…
user
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How is convex hull method used in outlier detection?
I think the slides are bit unclear on what they want to say. Can someone elaborate this with example.
0
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2 answers
Are cluster feature and micro-cluster good summary statistics for outlier detection in high dimensional data streams?
I'm dealing with outlier detection in data streams. I'm looking for a way to summarize my data and obtain important statistics such as means and variance, etc. I want to know if the cluster features or microclusters are suitable or not.
I Sui
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Anomaly Detection for Large Time Series Data
I am working on detecting anomalies within a large time series data set. It is updated on a regular basis and consists of more than 30 parameters. I am using R as a reference language.
It is a first for me working on this type of projects and I am…
Zaynab
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