diff --git a/classification/Logistic Regression.ipynb b/classification/Logistic Regression.ipynb index ddbab4627cf4a6d27acf6a1c454faa3ef1e05aba..fa21892f48feffe99e4d4d9932c787dfc5e529c9 100644 --- a/classification/Logistic Regression.ipynb +++ b/classification/Logistic Regression.ipynb @@ -28,10 +28,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(60000, 28, 28)\n", + "(10000, 28, 28)\n" + ] + } + ], + "source": [ + "from __future__ import print_function\n", "import mnist\n", "\n", "imgs_train = mnist.train_images()\n", @@ -54,9 +64,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x653ff90>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib\n", "import numpy as np\n", @@ -80,9 +101,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5, 0, 4, 1, 9, 2, 1, 3])" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "y_train[0:8]" ] @@ -98,18 +130,40 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 255)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.min(imgs_train), np.max(imgs_train)" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "33.318421449829934" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.mean(imgs_train)" ] @@ -123,9 +177,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(10000, 784)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def normalize_and_prepare(imgs):\n", " # normalize between -0.5 ... 0.5\n", @@ -163,9 +228,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x6ab1ad0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def sigmoid(z):\n", " return 1 / (1 + np.exp(-z))\n", @@ -208,7 +284,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -251,6 +327,26 @@ " # TODO: Compute the gradient. The resulting gradient has the following shape\n", " theta_grad = np.zeros(n_features + 1)\n", " \n", + " # add the constant bias feature\n", + " X_p = np.hstack((np.ones((m_samples, 1)), X))\n", + "\n", + " # compute activation\n", + " h = sigmoid(np.dot(X_p, theta))\n", + " cost = -y * np.log(h) - (1. - y) * np.log(1. - h)\n", + "\n", + " # we don't want to penalize the bias term\n", + " theta_no_bias = copy.copy(theta)\n", + " theta_no_bias[0] = 0.\n", + "\n", + " # regularized cost function\n", + " J = 1. / m_samples * np.sum(cost) + lam / (2 * m_samples) * np.sum(theta_no_bias**2)\n", + "\n", + " # compute gradient of d_J/d_theta\n", + " theta_grad = np.dot(X_p.T, (h - y)) / m_samples\n", + "\n", + " # add gradient for regularization\n", + " theta_grad += lam / m_samples * theta_no_bias\n", + " \n", " #### end your code ####\n", "\n", " return J, theta_grad" @@ -266,13 +362,21 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hooray, your loss function looks good\n" + ] + } + ], "source": [ "# this loads already theta values for all labels.\n", "# we want to check it however just for one label\n", - "theta_check = np.load('data/lr_theta_check.npy', allow_pickle=False)\n", + "theta_check = np.load('data/lr_theta_check.npy')\n", "\n", "# define a shorthand version of the loss function\n", "# We test only for the label 8\n", @@ -299,11 +403,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking gradient accuracy\n", + "Index i expect. grad[i] grad[i] rel. diff.\n", + " 95 -0.000907 -0.000907 3.5e-07\n", + " 96 -0.000957 -0.000957 5.3e-07\n", + " 97 -0.000892 -0.000892 5.8e-07\n", + " 98 -0.000881 -0.000881 6.8e-07\n", + " 99 -0.000861 -0.000861 4.7e-07\n", + " 100 -0.000961 -0.000961 4.3e-07\n", + " 101 -0.000823 -0.000823 4.6e-07\n", + " 102 -0.000848 -0.000848 4.5e-07\n", + " 103 -0.000822 -0.000822 2.3e-07\n", + " 104 -0.000860 -0.000860 5.2e-07\n", + "The gradient looks correct :)\n" + ] + } + ], "source": [ "import mytools\n", "# perform checking\n", @@ -323,9 +447,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Learned label 0 , Loss: 0.00992101770975\n" + ] + } + ], "source": [ "import scipy.optimize\n", "\n", @@ -353,9 +485,27 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Probabilities of beeing zero: [ 4.51387254e-07 9.99969138e-01 9.98267006e-01 1.69813963e-14]\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x6d7c5f0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, axes = plt.subplots(1, 4)\n", "\n", @@ -386,9 +536,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy of the 0 classifier in the test set: 98.74%\n" + ] + } + ], "source": [ "probability = lr_hypothesis(theta_trained, X_test)\n", "predicted = probability > 0.5\n", @@ -398,9 +556,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy of the 0 classifier in the training set: 99.82%\n" + ] + } + ], "source": [ "# What happens if we use the training set?\n", "probability = lr_hypothesis(theta_trained, X_train[0: n_train_samples, :])\n", @@ -420,7 +586,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -433,9 +599,26 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Learned label 0 , Loss: 0.00992101770975\n", + "Learned label 1 , Loss: 0.019844586591\n", + "Learned label 2 , Loss: 0.0537845279109\n", + "Learned label 3 , Loss: 0.058586958348\n", + "Learned label 4 , Loss: 0.0413742789508\n", + "Learned label 5 , Loss: 0.0556147478817\n", + "Learned label 6 , Loss: 0.0244813734732\n", + "Learned label 7 , Loss: 0.0370558972861\n", + "Learned label 8 , Loss: 0.0735227408002\n", + "Learned label 9 , Loss: 0.0765813298966\n" + ] + } + ], "source": [ "n_train_samples = 5000\n", "theta_all = train_multi_class(X_train[0:n_train_samples], y_train[0:n_train_samples], 10)" @@ -450,7 +633,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -476,9 +659,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x271a5eb0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, axes = plt.subplots(1, 8)\n", "fig.set_size_inches(18, 8)\n", @@ -491,9 +685,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([7, 2, 1, 0, 4, 1, 4, 9])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "predict_label(theta_all, X_test[0:8, :])" ] @@ -513,9 +718,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy of the logistic regression on the test set: 89.21%\n" + ] + } + ], "source": [ "labels_predicted = predict_label(theta_all, X_test)\n", "accuracy = np.mean(np.array(labels_predicted == y_test, dtype=float))\n", @@ -524,9 +737,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy of the logistic regression on the training set: 94.96%\n" + ] + } + ], "source": [ "labels_predicted = predict_label(theta_all, X_train[0:n_train_samples, :])\n", "accuracy = np.mean(np.array(labels_predicted == y_train[0:n_train_samples], dtype=float))\n", @@ -544,9 +765,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x2717b270>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, axes = plt.subplots(1, 10)\n", "fig.set_size_inches(18, 8)\n", @@ -554,27 +786,34 @@ "# show the first 8 images of the test set\n", "for i in range(0, 10):\n", " ax = axes[i]\n", - " ax.imshow(theta_all[1:, i].reshape((28,28)));" + " ax.imshow(theta_all[1:, i].reshape((28,28)), cmap='gray');" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 2", "language": "python", - "name": "python3" + "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 3 + "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.4" + "pygments_lexer": "ipython2", + "version": "2.7.14" } }, "nbformat": 4, diff --git a/classification/Neural Networks.ipynb b/classification/Neural Networks.ipynb index 7052c06a06546a09e6d5372e813d0562a510c5c2..0bb5f325b39fdf0e4811704c46a78d11e89c06d9 100644 --- a/classification/Neural Networks.ipynb +++ b/classification/Neural Networks.ipynb @@ -30,10 +30,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(60000, 28, 28)\n", + "(10000, 28, 28)\n" + ] + } + ], "source": [ + "from __future__ import print_function\n", "import mnist\n", "\n", "imgs_train = mnist.train_images()\n", @@ -47,9 +57,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x64adf90>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib\n", "import numpy as np\n", @@ -75,9 +96,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(10000, 784)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def normalize_and_prepare(imgs):\n", " # normalize between -0.5 ... 0.5\n", @@ -173,7 +205,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -214,6 +246,45 @@ " # The resulting gradient have the following shape\n", " theta_1_grad = np.zeros((n_features + 1, n_hidden_layer))\n", " theta_2_grad = np.zeros((n_hidden_layer + 1, n_labels))\n", + " \n", + " # add the constant bias feature\n", + " a_1 = np.hstack((np.ones((m_samples, 1)), X))\n", + "\n", + " # compute hidden layer activation\n", + " z_2 = np.dot(a_1, theta_1)\n", + " a_2 = sigmoid(z_2)\n", + " # add the constant bias feature\n", + " a_2 = np.hstack((np.ones((m_samples, 1)), a_2))\n", + "\n", + " z_3 = np.dot(a_2, theta_2)\n", + " a_3 = sigmoid(z_3)\n", + " h = a_3\n", + "\n", + " cost = -y * np.log(h) - (1. - y) * np.log(1. - h)\n", + "\n", + " # we don't want to penalize the bias term\n", + " theta_1[0, :] = 0.\n", + " theta_2[0, :] = 0\n", + "\n", + " # regularized cost function\n", + " J = 1. / m_samples * np.sum(cost) + lam / (2. * m_samples) * (np.sum(theta_1 ** 2) + np.sum(theta_2 ** 2))\n", + "\n", + " # start back-propagation / adjoint computation\n", + "\n", + " # error on output layer\n", + " z_3_grad = (h - y) / m_samples\n", + " theta_2_grad = np.dot(a_2.T, z_3_grad)\n", + "\n", + " a_2_grad = np.dot(theta_2, z_3_grad.T)\n", + " a_2_grad = a_2_grad[1:, :]\n", + "\n", + " # error on hidden layer\n", + " z_2_grad = a_2_grad.T * sigmoid_grad(z_2)\n", + " theta_1_grad = np.dot(a_1.T, z_2_grad)\n", + "\n", + " # add gradient for regularization\n", + " theta_1_grad += lam / m_samples * theta_1\n", + " theta_2_grad += lam / m_samples * theta_2\n", "\n", "\n", " ###### end your code #####\n", @@ -233,15 +304,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hooray, your loss function looks good\n" + ] + } + ], "source": [ "import mytools\n", "\n", "# this loads already theta values for all labels.\n", "# we want to check it however just for one label\n", - "theta_check = np.load('data/nn_theta_check.npy', allow_pickle=False)\n", + "theta_check = np.load('data/nn_theta_check.npy')\n", "\n", "my_loss_function = lambda theta:nn_loss_function(theta, X_train[0:5000],\n", " mytools.encode_one_hot(y_train[0:5000], 10),\n", @@ -266,9 +345,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking gradient accuracy\n", + "Index i expect. grad[i] grad[i] rel. diff.\n", + " 1 0.019655 0.019655 3.4e-07\n", + " 2 0.010370 0.010370 -1.7e-06\n", + " 3 -0.031734 -0.031734 5e-07\n", + " 4 -0.010173 -0.010173 1.8e-06\n", + " 5 -0.001620 -0.001620 4.1e-06\n", + " 6 -0.019257 -0.019257 2.5e-07\n", + " 19700 0.278354 0.278354 -4.5e-08\n", + " 19701 0.209945 0.209945 -9.6e-08\n", + " 19702 0.245652 0.245652 -8.3e-08\n", + " 19703 0.267370 0.267370 -6.9e-08\n", + " 19704 0.241570 0.241570 -5.6e-08\n", + "The gradient looks correct :)\n" + ] + } + ], "source": [ "import mytools\n", "# perform checking in the first and second layer\n", @@ -288,7 +388,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -312,7 +412,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -358,9 +458,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Training neural network... time to get a coffee\n", + "Warning: Maximum number of iterations has been exceeded.\n", + " Current function value: 0.048073\n", + " Iterations: 1000\n", + " Function evaluations: 1869\n", + " Gradient evaluations: 1869\n" + ] + } + ], "source": [ "n_hidden_layers = 25\n", "regularization = 0.1\n", @@ -383,7 +496,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -418,9 +531,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x6cac0b0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, axes = plt.subplots(1, 8)\n", "fig.set_size_inches(18, 8)\n", @@ -433,9 +557,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Prediction: [7 2 1 0 4 1 4 9]\n" + ] + } + ], "source": [ "prediction, probabilty = predict_label(theta_1, theta_2, X_test[0:8, :])\n", "print (\"Prediction: \", prediction)" @@ -450,9 +582,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Probability: [ 0.99998333 0.99976658 0.99772764 0.99996732 0.99985844 0.99971525\n", + " 0.99815947 0.99999699]\n" + ] + } + ], "source": [ "print (\"Probability: \", probabilty)" ] @@ -473,9 +614,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy of the neural network on the test set: 91.69%\n" + ] + } + ], "source": [ "labels_predicted, probability = predict_label(theta_1, theta_2, X_test)\n", "accuracy = np.mean(np.array(labels_predicted == y_test, dtype=float))\n", @@ -484,9 +633,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy of the neural network on the training set: 100%\n" + ] + } + ], "source": [ "labels_predicted, probability = predict_label(theta_1, theta_2, X_train[0:n_train_samples, :])\n", "accuracy = np.mean(np.array(labels_predicted == y_train[0:n_train_samples], dtype=float))\n", @@ -496,21 +653,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 2", "language": "python", - "name": "python3" + "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 3 + "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.4" + "pygments_lexer": "ipython2", + "version": "2.7.14" } }, "nbformat": 4,