Kaggle: Difference between revisions

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We're doing this kaggle comp
Noisebridge Kaggle team!!!!!!!!!!!!!!!!!!!!!!!!!!!!!


We use this wiki to archive information. We use this google group to communicate with each other:
https://groups.google.com/forum/#!forum/nbkaggle
The Noisebridge neuro hacking dream team has a lot of useful stuff on their reading list:
https://noisebridge.net/wiki/DreamTeam/Reading#Seizure_Detection
Here is a link to the competition:
https://www.kaggle.com/c/melbourne-university-seizure-prediction/data
https://www.kaggle.com/c/melbourne-university-seizure-prediction/data


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Ali Shoeb, John Guttag Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts, 02139
Ali Shoeb, John Guttag Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts, 02139


http://machinelearning.wustl.edu/mlpapers/paper_files/icml2010_ShoebG10.pdf
https://drive.google.com/open?id=0ByjOj5sb0Oj_SGduRjduNVdfX1k


EEG-based neonatal seizure detection with Support Vector Machines
EEG-based neonatal seizure detection with Support Vector Machines
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b Department of Electrical and Electronic Engineering, University College Cork, Ireland c Department of Paediatrics and Child Health, University College Cork, Ireland
b Department of Electrical and Electronic Engineering, University College Cork, Ireland c Department of Paediatrics and Child Health, University College Cork, Ireland


[[Eeg-svm.pdf]]
https://drive.google.com/open?id=0ByjOj5sb0Oj_UzVxdGpkcTNPV0E
 
 
= Code =
 
https://github.com/cowlicks/kaggle-seizure-prediction
 
== reading the data ==
Here is a python function to load a file from the matplotlib file format.
 
<nowiki>
 
from scipy.io import loadmat
 
def load(fn):
    return loadmat(fn, struct_as_record=False)['dataStruct'][0, 0].data
 
</nowiki>
 
<nowiki>
import pandas as pd
from scipy.io import loadmat
 
def mat_to_pandas(path):
    mat = loadmat(path)
    names = mat['dataStruct'].dtype.names
    ndata = {n: mat['dataStruct'][n][0, 0] for n in names}
    sequence = -1
    if 'sequence' in names:
        sequence = mat['dataStruct']['sequence']
    return pd.DataFrame(ndata['data'], columns=ndata['channelIndices'][0]), sequence
 
</nowiki>
via https://www.kaggle.com/zfturbo/melbourne-university-seizure-prediction/seizure-boost-0-6-lb/code

Latest revision as of 17:43, 21 September 2016

Noisebridge Kaggle team!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

We use this wiki to archive information. We use this google group to communicate with each other: https://groups.google.com/forum/#!forum/nbkaggle

The Noisebridge neuro hacking dream team has a lot of useful stuff on their reading list: https://noisebridge.net/wiki/DreamTeam/Reading#Seizure_Detection

Here is a link to the competition: https://www.kaggle.com/c/melbourne-university-seizure-prediction/data

Papers[edit]

Random papers from google searching "machine learning seizure detection"

Application of Machine Learning To Epileptic Seizure Detection

Ali Shoeb, John Guttag Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts, 02139

https://drive.google.com/open?id=0ByjOj5sb0Oj_SGduRjduNVdfX1k

EEG-based neonatal seizure detection with Support Vector Machines

A. Temko a,*, E. Thomas a, W. Marnane a,b, G. Lightbody a,b, G. Boylan a,c a Neonatal Brain Research Group, University College Cork, Ireland b Department of Electrical and Electronic Engineering, University College Cork, Ireland c Department of Paediatrics and Child Health, University College Cork, Ireland

https://drive.google.com/open?id=0ByjOj5sb0Oj_UzVxdGpkcTNPV0E


Code[edit]

https://github.com/cowlicks/kaggle-seizure-prediction

reading the data[edit]

Here is a python function to load a file from the matplotlib file format.


from scipy.io import loadmat

def load(fn):
    return loadmat(fn, struct_as_record=False)['dataStruct'][0, 0].data


import pandas as pd
from scipy.io import loadmat

def mat_to_pandas(path):
    mat = loadmat(path)
    names = mat['dataStruct'].dtype.names
    ndata = {n: mat['dataStruct'][n][0, 0] for n in names}
    sequence = -1
    if 'sequence' in names:
        sequence = mat['dataStruct']['sequence']
    return pd.DataFrame(ndata['data'], columns=ndata['channelIndices'][0]), sequence


via https://www.kaggle.com/zfturbo/melbourne-university-seizure-prediction/seizure-boost-0-6-lb/code