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'/home/parismita/mmit_data/autoprice/targets.csv',\n+\t\t\t'/home/parismita/mmit_data/baskball/features.csv', '/home/parismita/mmit_data/baskball/targets.csv',\n+\t\t\t'/home/parismita/mmit_data/bodyfat/features.csv', '/home/parismita/mmit_data/bodyfat/targets.csv',\n+\t\t\t'/home/parismita/mmit_data/cloud/features.csv', '/home/parismita/mmit_data/cloud/targets.csv',\n+\t\t\t'/home/parismita/mmit_data/cpu/features.csv', '/home/parismita/mmit_data/cpu/targets.csv',\n+\t\t\t'/home/parismita/mmit_data/meta/features.csv', '/home/parismita/mmit_data/meta/targets.csv' ,\n+\t\t\t'/home/parismita/mmit_data/sleep/features.csv', '/home/parismita/mmit_data/sleep/targets.csv']\n+\n+\n+for i in xrange(20):\n+\traw_data = open(filename[i], 'rt')\n+\treader = csv.reader(raw_data, delimiter=',', quoting=csv.QUOTE_NONE)\n+\tx = list(reader)\n+\to.append(np.array(x[1:]).astype('float'))\n+\n+for i in xrange(0,20,2):\n+\tx = o[i]\n+\ty = o[i + 1]\n+\n+\ttrainx = x[:len(x)/2,]\n+\ttrainy = y[:len(y)/2,]\n+\ttestx = x[len(x)/2:,]\n+\ttesty = y[len(y)/2:,]\n+\n+\testimator = MaxMarginIntervalTree(margin=1.0, 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