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%matplotlib inline


    

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%run ~/git/cc/tools/dsp/notebooks/notebook_setup_dsp.py


    

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from extractFeatures import *


    

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cd /Users/billpierce/audio/


    

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plt.rcParams['figure.figsize'] = (24.0, 16.0)


    

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label_features_map = get_label_features_map('dataset2', upper_frequency=150, number_bins=12)


    

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features_train, labels_train, features_test, labels_test = partition_dataset(label_features_map, train_fraction=0.8)


    

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plot_features_3d(features_train, labels_train)


    

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plot_features_3d(features_test, labels_test)


    

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from sklearn.tree import DecisionTreeClassifier
clf = DecisionTreeClassifier()
run_classifier(clf, features_train, labels_train, features_test, labels_test)


    

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from sklearn import svm
clf = svm.SVC(kernel='linear')
run_classifier(clf, features_train, labels_train, features_test, labels_test)


    

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from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClassifier(n_neighbors=10)
run_classifier(knn, features_train, labels_train, features_test, labels_test)


    

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from sklearn.neighbors.nearest_centroid import NearestCentroid
nc = NearestCentroid()
run_classifier(nc, features_train, labels_train, features_test, labels_test)


    

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