Discover and read the best of Twitter Threads about #WEKA
Most recents (2)
New #TrackMate version out (v&7)
With major changes and improvements I describe below (probably a long thread).
It is the product of a great (and cool) collaboration with @guijacquemet lab (@JwPylvanainen), the @DumenilLab lab in @institutpasteur and the IAH facility
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With major changes and improvements I describe below (probably a long thread).
It is the product of a great (and cool) collaboration with @guijacquemet lab (@JwPylvanainen), the @DumenilLab lab in @institutpasteur and the IAH facility
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The new version is the product of an almost Codiv19-induced full rewrite of TrackMate. Our main goal was to allow integrate SOTA segmentation algorithms and tools such as #StarDist, @ilastik_team, #Weka, @MorphoLibJ and #cellpose in TrackMate,
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so that they can be used in a tracking pipeline and improve the tracking accuracy and results.
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Automation Tools To Ease Your Data Science Project
Working on Data Science Project can be overwhelming for beginners esp student that intend to carry our a research in this field.
Below are some automation tools that data science professional can use.
#DataScience #Thread
Working on Data Science Project can be overwhelming for beginners esp student that intend to carry our a research in this field.
Below are some automation tools that data science professional can use.
#DataScience #Thread
1 WEKA
Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization
#WEKA help you discover practical data mining &learn to mine your own data
Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization
#WEKA help you discover practical data mining &learn to mine your own data
#WEKA make it easy for you to play around with data and it gives you test options regarding how you split your #dataset.
I once used WEKA to get result 'clue' for Classification of EEG signal using AIRS, Immuno, CLONALG.
Download WEKA: cs.waikato.ac.nz/ml/weka/
I once used WEKA to get result 'clue' for Classification of EEG signal using AIRS, Immuno, CLONALG.
Download WEKA: cs.waikato.ac.nz/ml/weka/
