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Results tagged with machine-learning
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user 54096
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
1
vote
Predicting time of event from multiple timeseries
This kind of problem can be modelled in two different ways, which I call time-of-event and time-to-event. The first is what you have tried out so far, and illustrated in your picture.
Time-of-event
Fe …
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0
votes
Classification on sound data
In the case of a mel-spectrogram preprocessing, the Short-Term Fourier Transform (STFT) followed by a mel-filterbank reduction and log-scaling is used. It transforms the 1 dimensional audio waveform i …
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4
votes
How to Justify Anomalies Detected by Unsupervised Anomaly Detection Models?
Your domain experts and other stakeholders are primary sources of information. Work them and work with them in order to find out what is an appropriate definition for "normal" and "abnormal". A key el …
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0
votes
Unsupervised anomaly detection - dataset with multiple users
For a strategy that treats each "group" (in your case a person) as independent, the most straightforward is indeed to create one model per group, each with its own set of parameters.
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0
votes
Time Series - Anomaly Detection
It is not possible to know what is the best model, method or library with so little information on the problem. The nature of anomalies, the performance targets, the computational requirements, the ne …
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2
votes
How does sklearn random forest use features in the form of 1D/2D array instead of a single v...
With RandomForest as it exists in scikit-learn, and practically all other implementations, there is no way to input structured data - be it 1D sequences or 2D matrices. All data must be transformed in …
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1
vote
Accepted
Gaussian Mixture Model performance with data outliers
Gaussian Mixture Models can struggle when there are outliers in the data - as the standard formulations will attempt to ensure that all datapoints are modeled by the Gaussian mixtures.
A common approa …
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0
votes
How do I determine the top "reason" for anomaly when using Isolation Forests
Since a while back one can use SHAP to exlain scikit-learn Isolation Forest models. Example code and output in this answer.
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1
vote
Accepted
Should I train the "Unknown" class separately from the other classes
There are several ways of doing this. Examples are:
Binary classifier
Train a separate binary classifier for Known vs Unknown, using supervised learning. The Known data would come from your dataset, a …
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1
vote
Accepted
Machine learning classification with time-domain signals how to ignore signal arrival time?
A common approach is what you suggest in 1. - apply time-shift as a Data Augmentation strategy. The augmentation is generally beneficial with deep learning models, and GPUs are fast so the compute tim …
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1
vote
I am trying to implement Isolation forest for anomaly detection but I am not able to underst...
According to this answer the range of output from scikit-learn IsolationForest decision_function is between -0.5 and 0.5, where smaller values mean more anomalous.
The predict function then applies a …
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3
votes
Machine learning in audio?
There is now a youtube channel dedicated to Audio Machine Learning, The Sound of AI. There is also an associated Slack community for discussions.
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1
vote
What are the audio features to best describe a music?
The features you have selected are a good starting point, but are still (with the exception of tempo) quite "low level" compared to what might be most relevant for music recommendation systems.
The Es …
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3
votes
Labelling a Time series dataset
Some feedback/tips/tricks/opinions here:
Problem setup
Including requirement analysis. Gotta decide how the system/solution should work, how to know ho how well we are doing, and then how to get there …
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0
votes
Machine learning on classifying speech
I would recommend to try a pretrained CNN to extract features, then do a simple classifier on top of that. OpenL3 for example is very easy to use, and performs pretty well on a range of tasks.
The cla …
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