moa data classfication

MOA_Data.py

@@ -0,0 +1,36 @@
+import os
+from sklearn.naive_bayes import GaussianNB
+from strlearn.streams import ARFFParser
+from sklearn.metrics import accuracy_score
+import matplotlib.pyplot as plt
+from scipy.signal import medfilt
+
+streams = os.listdir('data/moa')
+streams.remove('.DS_Store')
+print(streams)
+
+chunks = 500
+
+fig, ax = plt.subplots(4,3,figsize=(12,7), sharex=True, sharey=True)
+ax = ax.ravel()
+
+for s_id, s in enumerate(streams):
+    data = ARFFParser('data/moa/%s' % s)
+    clf = GaussianNB()
+    scores = []
+
+    for c in range(chunks):
+        X, y = data.get_chunk()
+        if c==0:
+            clf.fit(X, y)
+        else:
+            scores.append(accuracy_score(y, clf.predict(X)))
+
+    ax[s_id].plot(medfilt(scores,11))
+    ax[s_id].grid(ls=':')
+    ax[s_id].set_title(s.split('.')[0])
+    if s_id in [0,3,6,9]:
+       ax[s_id].set_ylabel('accuracy')
+
+    plt.tight_layout()
+    plt.savefig('foo.png')