nodeIdx, frequency, featureList,
rawIntervals)
filename = "C:/Users/yangy_000/Dropbox/BAYLOR/TEMP/NeuralSignalDecoding/NODE%d.csv" % i
featureDF.to_csv(filename)
#### Feature Testing(Only take one node with one frequency for example)
featureList = ['mean']
nodeIdx = [0]
frequency = ['Delta'] #, 'Theta', 'Alpha' ,'Beta' ,'Low Gamma', 'High Gamma']
# Generation
featureDF = FeatureGeneration.FeatureDF(ecogTrainScaled, sentenceTrain,
nodeIdx, frequency, featureList,
rawIntervals)
# Accuracy testing
FeatureGeneration.FeatureVisualCheck(featureDF)
#==============================================================================
# Data Visualization (Visualized by Dimension reduciton)
#==============================================================================
# parameters
n_neighbors = 10
n_components = 2 # number of reduced dimensions
# t-SNE method(dimension reduction techniques)
Visualization.DimensionReduction(n_neighbors, n_components, featureDF)
#==============================================================================
# Classification (Take SVM as an example)
#==============================================================================
trainProp = 0.6 # training datasize
Classification.SVMClassification(featureDF, trainProp)
