[DOC] Add scripts on producing experiment result

Author: xuyxu

docs/plotting/lenet_cifar10.py

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+import matplotlib.pyplot as plt
+
+plt.style.use("seaborn")
+
+n_estimators = [5, 10, 15, 20]
+fusion = [78.26, 78.79, 78.44, 77.20]
+voting = [77.71, 78.22, 78.13, 78.73]
+bagging = [77.15, 77.32, 77.52, 77.85]
+gradient_boosting = [77.28, 78.88, 79.19, 78.60]
+snapshot_ensemble = [70.83, 70.69, 70.06, 70.37]
+
+plt.plot(n_estimators, fusion, label="fusion", linewidth=5)
+plt.plot(n_estimators, voting, label="voting", linewidth=5)
+plt.plot(n_estimators, bagging, label="bagging", linewidth=5)
+plt.plot(n_estimators, gradient_boosting, label="gradient boosting", linewidth=5)
+plt.plot(n_estimators, snapshot_ensemble, label="snapshot ensemble", linewidth=5)
+
+plt.title("LeNet@CIFAR-10", fontdict={"size": 30})
+plt.xlabel("n_estimators", fontdict={"size": 30})
+plt.ylabel("testing acc", fontdict={"size": 30})
+plt.xticks(n_estimators, fontsize=25)
+plt.yticks(fontsize=25)
+plt.legend(prop={"size": 30})

docs/plotting/lenet_mnist.py

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+import matplotlib.pyplot as plt
+
+plt.style.use("seaborn")
+
+n_estimators = [5, 10, 15, 20]
+fusion = [99.16, 99.24, 99.20, 99.23]
+voting = [99.47, 99.47, 99.51, 99.52]
+bagging = [99.47, 99.52, 99.52, 99.54]
+gradient_boosting = [99.13, 99.53, 99.51, 99.43]
+snapshot_ensemble = [99.22, 99.25, 99.28, 99.32]
+
+plt.plot(n_estimators, fusion, label="fusion", linewidth=5)
+plt.plot(n_estimators, voting, label="voting", linewidth=5)
+plt.plot(n_estimators, bagging, label="bagging", linewidth=5)
+plt.plot(n_estimators, gradient_boosting, label="gradient boosting", linewidth=5)
+plt.plot(n_estimators, snapshot_ensemble, label="snapshot ensemble", linewidth=5)
+
+plt.title("LeNet@MNIST", fontdict={"size": 30})
+plt.xlabel("n_estimators", fontdict={"size": 30})
+plt.ylabel("testing acc", fontdict={"size": 30})
+plt.xticks(n_estimators, fontsize=25)
+plt.yticks(fontsize=25)
+plt.legend(prop={"size": 30})

docs/plotting/resnet_cifar10.py

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+import matplotlib.pyplot as plt
+
+plt.style.use("seaborn")
+
+n_estimators = [2, 5, 7, 10]
+fusion = [95.32, 95.34, 95.31, 95.29]
+voting = [96.00, 94.77, 96.41, 95.34]
+bagging = [95.71, 94.97, 96.16, 94.94]
+gradient_boosting = [95.63, 95.78, 95.77, 96.03]
+snapshot_ensemble = [95.57, 95.71, 96.34, 95.68]
+
+plt.plot(n_estimators, fusion, label="fusion", linewidth=5)
+plt.plot(n_estimators, voting, label="voting", linewidth=5)
+plt.plot(n_estimators, bagging, label="bagging", linewidth=5)
+plt.plot(n_estimators, gradient_boosting, label="gradient boosting", linewidth=5)
+plt.plot(n_estimators, snapshot_ensemble, label="snapshot ensemble", linewidth=5)
+
+plt.title("ResNet@CIFAR-10", fontdict={"size": 30})
+plt.xlabel("n_estimators", fontdict={"size": 30})
+plt.ylabel("testing acc", fontdict={"size": 30})
+plt.xticks(n_estimators, fontsize=25)
+plt.yticks(fontsize=25)
+plt.legend(prop={"size": 30})