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@JiaweiZhuang
Created August 16, 2018 03:41
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Predict uncertainty on simple function
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"import torch\n",
"from torch.utils.data import DataLoader, TensorDataset"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x11892d898>]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataset = 0\n",
"#dataset = 1\n",
" \n",
"if dataset == 0:\n",
" # data used by https://github.com/muupan/deep-ensemble-uncertainty\n",
" x_train = np.linspace(-5, 5, 100, dtype=np.float32).reshape(-1,1)\n",
" y_train = np.cos(x_train)\n",
"\n",
" x_test = np.linspace(-10, 10, 200, dtype=np.float32).reshape(-1,1)\n",
" y_test = np.cos(x_test)\n",
" \n",
"elif dataset == 1:\n",
" # data used by https://fairyonice.github.io/Measure-the-uncertainty-in-deep-learning-models-using-dropout.html\n",
" # this doesn't work very well...\n",
" true_func = lambda x: np.sin(2*np.pi*x) - x\n",
" \n",
" inc = 0.05\n",
" x_train =np.concatenate([np.arange(-2,-1.5,0.02, dtype=np.float32),\n",
" np.arange(-1,0.5,0.05, dtype=np.float32)\n",
" ]).reshape(-1,1)\n",
" y_train = true_func(x_train)\n",
"\n",
" x_test = np.linspace(-3, 2, 200, dtype=np.float32).reshape(-1,1)\n",
" y_test = true_func(x_test)\n",
"\n",
"plt.plot(x_test, y_test, alpha=0.3)\n",
"plt.plot(x_train, y_train, '.')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# convenience function for NN prediction\n",
"predict_model = lambda model, x: model(torch.from_numpy(x)).detach().numpy()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Naive ensemble"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def MLP(H1=10, H2=10, act=torch.nn.ReLU() ):\n",
" model = torch.nn.Sequential(\n",
" torch.nn.Linear(1, H1),\n",
" act,\n",
" torch.nn.Linear(H1, H2),\n",
" act,\n",
" torch.nn.Linear(H2, 1),\n",
" )\n",
" return model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Full batch GD"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def training_GD(model, x=x_train, y=y_train, n_epoch=5000, i_print=1000):\n",
" \"\"\"\n",
" Full batch gradient descend\n",
" \"\"\"\n",
" x_torch = torch.from_numpy(x)\n",
" y_torch = torch.from_numpy(y)\n",
" \n",
" loss_fn = torch.nn.MSELoss()\n",
" optimizer = torch.optim.Adam(model.parameters())\n",
"\n",
" for t in range(n_epoch):\n",
" optimizer.zero_grad()\n",
" y_pred = model(x_torch)\n",
" loss = loss_fn(y_pred, y_torch)\n",
" loss.backward()\n",
" optimizer.step()\n",
"\n",
" if (t+1)%i_print==0:\n",
" print(t+1, ',', '{:2.2e}'.format(loss.item()), end=' | ')\n",
" \n",
" print('done')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1000 , 1.16e-03 | 2000 , 4.72e-04 | 3000 , 3.66e-04 | 4000 , 3.21e-04 | 5000 , 3.01e-04 | done\n",
"1000 , 5.41e-03 | 2000 , 2.61e-04 | 3000 , 1.67e-04 | 4000 , 1.46e-04 | 5000 , 1.39e-04 | done\n",
"1000 , 5.98e-04 | 2000 , 5.07e-04 | 3000 , 4.89e-04 | 4000 , 4.65e-04 | 5000 , 4.38e-04 | done\n",
"1000 , 1.81e-02 | 2000 , 4.97e-04 | 3000 , 3.58e-04 | 4000 , 2.91e-04 | 5000 , 2.47e-04 | done\n",
"1000 , 2.74e-02 | 2000 , 5.41e-04 | 3000 , 1.96e-04 | 4000 , 1.36e-04 | 5000 , 1.14e-04 | done\n",
"1000 , 8.67e-03 | 2000 , 1.32e-03 | 3000 , 8.13e-04 | 4000 , 7.33e-04 | 5000 , 7.12e-04 | done\n",
"1000 , 1.12e-03 | 2000 , 3.25e-04 | 3000 , 2.79e-04 | 4000 , 2.57e-04 | 5000 , 2.44e-04 | done\n",
"1000 , 5.25e-03 | 2000 , 9.97e-04 | 3000 , 5.78e-04 | 4000 , 5.50e-04 | 5000 , 5.27e-04 | done\n",
"1000 , 1.07e-02 | 2000 , 5.04e-04 | 3000 , 2.15e-04 | 4000 , 1.45e-04 | 5000 , 1.24e-04 | done\n",
"1000 , 4.86e-02 | 2000 , 4.28e-02 | 3000 , 4.27e-02 | 4000 , 4.27e-02 | 5000 , 4.27e-02 | done\n"
]
}
],
"source": [
"model_ensemble_1 = [MLP() for _ in range(10)]\n",
"\n",
"for model in model_ensemble_1:\n",
" training_GD(model)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"y_pred_ensemble_1 = [predict_model(model, x_test) for model in model_ensemble_1]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"for y_p in y_pred_ensemble_1:\n",
" plt.plot(x_test, y_p, c='b', alpha=0.4)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"pred_mean_1 = np.mean(y_pred_ensemble_1, axis=0)\n",
"pred_std_1 = np.std(y_pred_ensemble_1, axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x11f83b940>]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"plt.plot(x_test, pred_mean_1)\n",
"plt.plot(x_test, pred_mean_1+pred_std_1*3)\n",
"plt.plot(x_test, pred_mean_1-pred_std_1*3)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x11f8a6128>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(pred_std_1, np.abs(y_test-pred_mean_1), alpha=0.3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## SGD"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def training_SGD(model, x=x_train, y=y_train, batch_size=16, n_epoch=1000, i_print=200):\n",
" \"\"\"mini-batch SGD\"\"\"\n",
" x_torch = torch.from_numpy(x)\n",
" y_torch = torch.from_numpy(y)\n",
" dataloader = DataLoader(dataset=TensorDataset(x_torch, y_torch), \n",
" batch_size=batch_size, shuffle=True)\n",
" \n",
" loss_fn = torch.nn.MSELoss()\n",
" optimizer = torch.optim.Adam(model.parameters())\n",
" \n",
" for t in range(n_epoch):\n",
" \n",
" for step, (batch_x, batch_y) in enumerate(dataloader): \n",
" optimizer.zero_grad()\n",
" y_pred = model(batch_x)\n",
" loss = loss_fn(y_pred, batch_y)\n",
" loss.backward()\n",
" optimizer.step()\n",
"\n",
" if (t+1)%i_print==0:\n",
" print(t+1, ',', '{:2.2e}'.format(loss.item()), end=' | ') # this is just the average loss on a mini-batch\n",
" \n",
" print('done')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"200 , 1.01e-03 | 400 , 7.58e-03 | 600 , 3.08e-04 | 800 , 1.01e-04 | 1000 , 1.17e-04 | done\n",
"200 , 8.25e-02 | 400 , 3.75e-04 | 600 , 1.90e-03 | 800 , 5.99e-04 | 1000 , 1.24e-03 | done\n",
"200 , 4.83e-02 | 400 , 7.71e-05 | 600 , 3.94e-03 | 800 , 4.17e-04 | 1000 , 1.08e-04 | done\n",
"200 , 3.85e-02 | 400 , 3.46e-04 | 600 , 6.57e-05 | 800 , 8.47e-05 | 1000 , 1.37e-04 | done\n",
"200 , 7.12e-02 | 400 , 8.85e-05 | 600 , 2.36e-03 | 800 , 5.18e-04 | 1000 , 2.19e-04 | done\n",
"200 , 1.97e-02 | 400 , 1.01e-04 | 600 , 2.71e-04 | 800 , 8.81e-04 | 1000 , 3.95e-04 | done\n",
"200 , 6.84e-02 | 400 , 1.24e-02 | 600 , 9.23e-05 | 800 , 7.33e-04 | 1000 , 1.53e-04 | done\n",
"200 , 7.01e-04 | 400 , 3.43e-04 | 600 , 4.45e-05 | 800 , 1.02e-03 | 1000 , 1.80e-04 | done\n",
"200 , 3.86e-02 | 400 , 2.21e-03 | 600 , 2.43e-04 | 800 , 3.85e-04 | 1000 , 4.75e-04 | done\n",
"200 , 1.02e-02 | 400 , 2.20e-04 | 600 , 1.96e-04 | 800 , 7.21e-05 | 1000 , 1.37e-04 | done\n"
]
}
],
"source": [
"model_ensemble_2 = [MLP() for _ in range(10)]\n",
"\n",
"for model in model_ensemble_2:\n",
" training_SGD(model)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"y_pred_ensemble_2 = [predict_model(model, x_test) for model in model_ensemble_2]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"for y_p in y_pred_ensemble_2:\n",
" plt.plot(x_test, y_p, c='b', alpha=0.4)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"pred_mean_2 = np.mean(y_pred_ensemble_2, axis=0)\n",
"pred_std_2 = np.std(y_pred_ensemble_2, axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x11facd518>]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"plt.plot(x_test, pred_mean_2)\n",
"plt.plot(x_test, pred_mean_2+pred_std_2*3)\n",
"plt.plot(x_test, pred_mean_2-pred_std_2*3)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x11fb2c400>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(pred_std_2, np.abs(y_test-pred_mean_2), alpha=0.3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## L-BFGS"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"def training_LBFGS(model, x=x_train, y=y_train, n_epoch=200, i_print=40):\n",
" \"\"\"\n",
" Full batch gradient descend\n",
" \"\"\"\n",
" x_torch = torch.DoubleTensor(x)\n",
" y_torch = torch.DoubleTensor(y)\n",
" \n",
" loss_fn = torch.nn.MSELoss()\n",
" optimizer = torch.optim.LBFGS(model.parameters())\n",
" for t in range(n_epoch):\n",
"\n",
" def closure():\n",
" optimizer.zero_grad()\n",
" y_pred = model(x_torch)\n",
" loss = loss_fn(y_pred, y_torch)\n",
" loss.backward()\n",
" return loss\n",
" optimizer.step(closure)\n",
"\n",
" if (t+1)%i_print==0:\n",
" y_pred = model(x_torch)\n",
" loss = loss_fn(y_pred, y_torch)\n",
" print(t+1, loss.item())"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"40 5.828289040531407e-07\n",
"80 5.557473349265041e-07\n",
"120 5.412671716813446e-07\n",
"160 5.330037289529577e-07\n",
"200 5.275685965932333e-07\n",
"40 5.065575558089581e-07\n",
"80 5.050712338683677e-07\n",
"120 5.042161771095167e-07\n",
"160 5.037213808388871e-07\n",
"200 5.034256070158692e-07\n",
"40 3.444791023854422e-07\n",
"80 3.4392867278058066e-07\n",
"120 3.4351239145401673e-07\n",
"160 3.431375707595079e-07\n",
"200 3.427777936805853e-07\n",
"40 2.720802936264889e-06\n",
"80 2.705675033086523e-06\n",
"120 2.695890468577419e-06\n",
"160 2.688326053422195e-06\n",
"200 2.6818611154041514e-06\n",
"40 1.6125295101762361e-06\n",
"80 1.6120407825470913e-06\n",
"120 1.6115525256254781e-06\n",
"160 1.6110647379032414e-06\n",
"200 1.6105774186940176e-06\n",
"40 0.18423951520552706\n",
"80 0.18423951520552706\n",
"120 0.18423951520552706\n",
"160 0.18423951520552706\n",
"200 0.18423951520552706\n",
"40 2.3171324424150976e-07\n",
"80 2.235276217676631e-07\n",
"120 2.2220950106572162e-07\n",
"160 2.210341011714108e-07\n",
"200 2.199213539191953e-07\n",
"40 3.033366197450215e-07\n",
"80 3.022220991022674e-07\n",
"120 3.0147346769517634e-07\n",
"160 3.009758838548422e-07\n",
"200 3.0064613514198283e-07\n",
"40 2.2036209358606136e-06\n",
"80 2.2011760356131995e-06\n",
"120 2.1987432297611788e-06\n",
"160 2.1963145993156694e-06\n",
"200 2.1938897776613014e-06\n",
"40 2.369126511416282e-06\n",
"80 2.3310646956464818e-06\n",
"120 2.2955346041505928e-06\n",
"160 2.2623590124378933e-06\n",
"200 2.2313629948525634e-06\n"
]
}
],
"source": [
"# L-BFGS tend to break at single precision or with Relu activation\n",
"model_ensemble_3 = [MLP(act=torch.nn.Tanh()).double() for _ in range(10)]\n",
"\n",
"for model in model_ensemble_3:\n",
" training_LBFGS(model)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"predict_model_d = lambda model, x: model(torch.DoubleTensor(x)).detach().numpy()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"y_pred_ensemble_3 = [predict_model_d(model, x_test) for model in model_ensemble_3]"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"pred_mean_3 = np.mean(y_pred_ensemble_3, axis=0)\n",
"pred_std_3 = np.std(y_pred_ensemble_3, axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-5, 5)"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"for y_p in y_pred_ensemble_3:\n",
" plt.plot(x_test, y_p, c='b', alpha=0.4)\n",
" \n",
"plt.ylim(-5,5)\n",
"# either very accurate or very bad (stuck at local minimum)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-2, 10)"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"plt.plot(x_test, pred_mean_3)\n",
"plt.plot(x_test, pred_mean_3+pred_std_3*3)\n",
"plt.plot(x_test, pred_mean_3-pred_std_3*3)\n",
"\n",
"plt.ylim(-2,10)\n",
"\n",
"# not a useful indicator of error..."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Dropout as uncertainty estimate\n",
"\n",
"- http://www.cs.ox.ac.uk/people/yarin.gal/website/blog_3d801aa532c1ce.html\n",
"- https://fairyonice.github.io/Measure-the-uncertainty-in-deep-learning-models-using-dropout.html\n",
"- https://github.com/yaringal/pytorch-practice/blob/master/Pytorch%2BUncertainity.ipynb"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"H1, H2 = 20, 20\n",
"dropout_rate = 0.1\n",
"\n",
"model_dropout = torch.nn.Sequential(\n",
" torch.nn.Linear(1, H1),\n",
" torch.nn.ReLU(),\n",
" torch.nn.Dropout(dropout_rate),\n",
" torch.nn.Linear(H1, H2),\n",
" torch.nn.ReLU(),\n",
" torch.nn.Dropout(dropout_rate),\n",
" torch.nn.Linear(H2, 1),\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1000 , 5.05e-02 | 2000 , 1.63e-02 | 3000 , 2.04e-02 | 4000 , 2.52e-02 | 5000 , 3.03e-02 | done\n"
]
}
],
"source": [
"training_GD(model_dropout)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Disable dropout\n",
"model_dropout.eval()\n",
"model_dropout.training"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x11f9e5f28>]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test)\n",
"plt.plot(x_test, predict_model(model_dropout, x_test))"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# keep doing dropout during testing\n",
"# https://discuss.pytorch.org/t/question-about-dropout/921\n",
"\n",
"model_dropout.train()\n",
"model_dropout.training"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1209390b8>]"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test)\n",
"plt.plot(x_test, predict_model(model_dropout, x_test))"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"y_pred_ensemble_4 = [predict_model(model_dropout, x_test) for _l in range(10)]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"for y_p in y_pred_ensemble_4:\n",
" plt.plot(x_test, y_p, c='b', alpha=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"pred_std_4 = np.std(y_pred_ensemble_4, axis=0)\n",
"pred_mean_4 = np.mean(y_pred_ensemble_4, axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x120a6cf60>]"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x_test, y_test, c='k')\n",
"\n",
"plt.plot(x_test, pred_mean_4)\n",
"plt.plot(x_test, pred_mean_4+pred_std_4)\n",
"plt.plot(x_test, pred_mean_4-pred_std_4)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x120b374e0>"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(pred_std_4, np.abs(y_test-pred_mean_4), alpha=0.3)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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