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Connectomics: Predicting the directed connections between 1,000 neurons using neural activity time series data

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Initial code pulled from http://mlwave.com/kaggle-connectomics-python-benchmark-code/

To produce predictions with AUC calculated, open a command line prompt and run:

python model.py [fluorescence data] [network positions] [true network configuration]
python model.py ../data/fluorescence_iNet1_Size100_CC01inh.txt ../data/networkPositions_iNet1_Size100_CC03inh.txt ../data/network_iNet1_Size100_CC01inh.txt
python model.py ../data/normal-4/fluorescence_normal-4.txt ../data/normal-4/networkPositions_normal-4.txt ../data/normal-4/network_normal-4.txt

To produce predictions without AUC, simply remove the last command line argument.

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Connectomics: Predicting the directed connections between 1,000 neurons using neural activity time series data

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