GitHub - dal3006/AnomaliesDetection-with-TimeSeriesAnalysis: This is an experimental of anomalies detection by applying different approach to the problem. PCA component regularization method, K-Mean Clustering, SVM and Gausian Distribution models has been used to detect anomalies on time series data.

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This is an experimental of anomalies detection by applying different approach to the problem. PCA component regularization method, K-Mean Clustering, SVM and Gausian Distribution models has been used to detect anomalies on time series data.

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.ipynb_checkpoints		.ipynb_checkpoints
data/data		data/data
results		results
.gitattributes		.gitattributes
AnomaliesDetection on TimeSeries_Data (MachineLearning part).ipynb		AnomaliesDetection on TimeSeries_Data (MachineLearning part).ipynb
Expedia_USA_hotel.csv		Expedia_USA_hotel.csv
readme.txt		readme.txt

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Note: 
    csv_database.db takes approximatelly 1.5GB and for that reason
    is not available directy on the github.

    Download full data from: https://www.kaggle.com/c/expedia-personalized-sort/data