From a53b6b7424e1bbadb0f97f7870949fa4d1d88324 Mon Sep 17 00:00:00 2001
From: "andreas.zimmermann" <andreas.zimmermann@stud.hslu.ch>
Date: Mon, 25 Sep 2023 12:56:51 +0200
Subject: [PATCH] try to push

---
 .../Gradient Descent.ipynb                    | 216 +++++++++++++++---
 .../Logistic Regression.ipynb                 | 147 ++++++++++--
 2 files changed, 311 insertions(+), 52 deletions(-)

diff --git a/notebooks/04B Gradient Descent/Gradient Descent.ipynb b/notebooks/04B Gradient Descent/Gradient Descent.ipynb
index a5379df..db9e626 100644
--- a/notebooks/04B Gradient Descent/Gradient Descent.ipynb	
+++ b/notebooks/04B Gradient Descent/Gradient Descent.ipynb	
@@ -1175,10 +1175,10 @@
    "source": [
     "# z-normalise the training and test data.\n",
     "\"\"\"\n",
-    "STIMMT NICHT! --> WIESO WIRD DER X_TRAIN VEKTOR SKALIERT UND DER Y_TEST VEKTOR?\n",
+    "STIMMT NICHT!\n",
     "scaler = StandardScaler()\n",
     "X_train_house_scaled = scaler.fit_transform(X_train_house_scaled)\n",
-    "y_test_house_scaled = scaler.transform(y_test_house_scaled.reshape(-1, 1))\n",
+    "X_test_house_scaled = scaler.transform(y_test_house_scaled.reshape(-1, 1))\n",
     "\"\"\""
    ]
   },
@@ -1290,13 +1290,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e630eaae5c0b4a94a619ead99a110b70",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(IntSlider(value=1, description='epoch', max=300, min=1), Output()), _dom_classes=('widge…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "@interact(epoch=(1, len(hist_house_scaled[\"theta0\"])))\n",
     "def visualize_learning(epoch=1):\n",
-    "    ax = sns.scatterplot(X_train_house_scaled, y_train_house_scaled)\n",
+    "    ax = sns.scatterplot(X_train_house_scaled, y=y_train_house_scaled)\n",
     "    plot_regression_line(X_train_house_scaled, \n",
     "                         hist_house_scaled[\"theta0\"][epoch-1], \n",
     "                         hist_house_scaled[\"theta1\"][epoch-1], ax)\n",
@@ -1313,13 +1328,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {
     "solution2": "hidden",
     "solution2_first": true
    },
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "R2:  0.5263014538841415\n"
+     ]
+    }
+   ],
+   "source": [
+    "r2 = r2_score(y_true=y_test_house_scaled, y_pred=predict(X_test_house_scaled, theta0, theta1))\n",
+    "print(\"R2: \", r2)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -1356,7 +1382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1412,7 +1438,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 44,
    "metadata": {
     "solution2": "hidden",
     "solution2_first": true
@@ -1421,7 +1447,7 @@
    "source": [
     "def predict(X, bias, thetas):\n",
     "    # START YOUR CODE\n",
-    "    \n",
+    "    y_pred = bias + np.dot(X, thetas)\n",
     "    # END YOUR CODE\n",
     "    return y_pred"
    ]
@@ -1464,13 +1490,15 @@
    },
    "outputs": [],
    "source": [
+    "\"\"\"\n",
+    "VERSTEH ICH NICHT!\n",
     "def gradient(X, y, bias, thetas):\n",
     "    # START YOUR CODE\n",
     "    \n",
     "    \n",
     "    \n",
     "    # END YOUR CODE\n",
-    "    return grad_bias, grad_thetas"
+    "    return grad_bias, grad_thetas\"\"\""
    ]
   },
   {
@@ -1482,7 +1510,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {
     "jupyter": {
      "source_hidden": true
@@ -1513,7 +1541,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1543,9 +1571,50 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f61227a0691242278037579707ee3f26",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 50 - cost: 1.4e+08 - r2: -0.198\n",
+      "Epoch 100 - cost: 7e+07 - r2: 0.4164\n",
+      "Epoch 150 - cost: 4.5e+07 - r2: 0.6264\n",
+      "Epoch 200 - cost: 3.6e+07 - r2: 0.7027\n",
+      "Epoch 250 - cost: 3.2e+07 - r2: 0.7313\n",
+      "Epoch 300 - cost: 3.1e+07 - r2: 0.7423\n",
+      "Epoch 350 - cost: 3e+07 - r2: 0.7468\n",
+      "Epoch 400 - cost: 3e+07 - r2: 0.7487\n",
+      "Epoch 450 - cost: 3e+07 - r2: 0.7496\n",
+      "Epoch 500 - cost: 3e+07 - r2: 0.7501\n",
+      "Epoch 550 - cost: 3e+07 - r2: 0.7504\n",
+      "Epoch 600 - cost: 3e+07 - r2: 0.7506\n",
+      "Epoch 650 - cost: 3e+07 - r2: 0.7508\n",
+      "Epoch 700 - cost: 3e+07 - r2: 0.7509\n",
+      "Epoch 750 - cost: 3e+07 - r2: 0.751\n",
+      "Epoch 800 - cost: 3e+07 - r2: 0.7511\n",
+      "Epoch 850 - cost: 3e+07 - r2: 0.7511\n",
+      "Epoch 900 - cost: 3e+07 - r2: 0.7512\n",
+      "Epoch 950 - cost: 3e+07 - r2: 0.7512\n",
+      "Epoch 1000 - cost: 3e+07 - r2: 0.7512\n"
+     ]
+    }
+   ],
    "source": [
     "alpha = 0.01\n",
     "num_epochs = 1000\n",
@@ -1554,9 +1623,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "def plot_validation_curves(hist, ylim=None):\n",
     "    fig, ax = plt.subplots(ncols=2, figsize=(16,5))\n",
@@ -1585,9 +1665,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 49,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "R2: 0.7477926795652788\n"
+     ]
+    }
+   ],
    "source": [
     "y_pred_autoscout = predict(X_test_autoscout, bias, thetas)\n",
     "r2 = r2_score(y_test_autoscout, y_pred_autoscout)\n",
@@ -1617,7 +1705,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 50,
    "metadata": {
     "solution2": "hidden",
     "solution2_first": true
@@ -1678,7 +1766,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 51,
    "metadata": {
     "code_folding": [],
     "jupyter": {
@@ -1751,9 +1839,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 52,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "18efe6d743e3453fa98778f09f38e5d7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/50 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 50 - train_cost: 1.4e+08 - train_r2: -0.1979\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "alpha = 1e-2\n",
     "num_epochs = 50\n",
@@ -1782,9 +1902,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 53,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "db55a6f04675420dbf157b6abee0b401",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/50 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 50 - train_cost: 3e+07 - train_r2: 0.7512\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "alpha = 1e-2\n",
     "num_epochs = 50\n",
@@ -1811,9 +1963,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 54,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "R2: 0.7477981521123799\n"
+     ]
+    }
+   ],
    "source": [
     "y_pred_autoscout = predict(X_test_autoscout, bias, thetas)\n",
     "r2 = r2_score(y_test_autoscout, y_pred_autoscout)\n",
diff --git a/notebooks/05A Classification/Logistic Regression.ipynb b/notebooks/05A Classification/Logistic Regression.ipynb
index 58a2420..1b54522 100644
--- a/notebooks/05A Classification/Logistic Regression.ipynb	
+++ b/notebooks/05A Classification/Logistic Regression.ipynb	
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "scrolled": true
    },
@@ -48,9 +48,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([4.33488598, 6.49116527, 4.65294084, 5.15294491, 5.11547596,\n",
+       "       5.021137  , 3.67806326, 5.359983  , 4.47380202, 5.44619487,\n",
+       "       4.93850052, 5.75285439, 4.15163543, 5.24912886, 5.47153976,\n",
+       "       5.9949529 , 5.49450444, 4.87397538, 4.6407758 ])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "students_passed = np.random.normal(5,0.7,100)\n",
     "students_passed[1:20]"
@@ -58,9 +72,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1.82134404, 2.99349548, 2.47933959, 1.78562475, 1.64010294,\n",
+       "       2.50721266, 3.4838347 , 1.14455083, 1.83820623, 1.0776492 ,\n",
+       "       1.99052302, 2.1228556 , 2.65436168, 1.48838012, 1.61971417,\n",
+       "       2.93017764, 2.12009927, 2.13217097, 1.2925187 ])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "students_failed = np.random.normal(2,0.7,100)\n",
     "students_failed[1:20]"
@@ -75,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -97,12 +125,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "legend_map = {0: 'failed', 1: 'passed'}\n",
-    "ax = sns.scatterplot(X, y, hue=pd.Series(y).map(legend_map))\n",
+    "\n",
+    "ax = sns.scatterplot(x=X, y=y, hue=pd.Series(y).map(legend_map))\n",
     "ax.set_xlabel('days spent learning for the ML exam')\n",
     "ax.set_ylabel('if students passed')\n",
     "plt.show()"
@@ -130,7 +170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {
     "solution2": "hidden",
     "solution2_first": true
@@ -139,7 +179,7 @@
    "source": [
     "def sigmoid(z):\n",
     "    # START YOUR CODE\n",
-    "    \n",
+    "    s = 1 / (1 + np.exp(-z))\n",
     "    # END YOUR CODE\n",
     "    return s"
    ]
@@ -163,6 +203,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "def sigmoid(z):\n",
     "    s = 1 / (1 + np.exp(-z))\n",
     "    return s"
@@ -170,9 +211,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x135fa339450>]"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "x = np.linspace(-8, 8)\n",
     "plt.plot(x, sigmoid(x))"
@@ -187,7 +249,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
     "solution2": "hidden",
     "solution2_first": true
@@ -196,7 +258,9 @@
    "source": [
     "def predict(X, theta0, theta1):\n",
     "    # START YOUR CODE\n",
-    "\n",
+    "    z = theta0 + theta1 * X\n",
+    "    y_pred = sigmoid(z)\n",
+    "    # y_pred = [0 if i < 0.5 else 1 for i in y_pred]\n",
     "    # END YOUR CODE\n",
     "    return y_pred"
    ]
@@ -220,6 +284,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "def predict(X, theta0, theta1):\n",
     "    z = theta0 +  theta1 * X\n",
     "    y_pred = sigmoid(z)\n",
@@ -228,9 +293,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.99875469, 0.99520267, 0.99944232, 0.99650507, 0.99787731,\n",
+       "       0.99779644, 0.99757897, 0.99078864, 0.99827359, 0.99582228,\n",
+       "       0.99841597, 0.99737095, 0.99883382, 0.9942434 , 0.99807159,\n",
+       "       0.99845555, 0.99908434, 0.99849056, 0.99719621, 0.99646245])"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "theta0 = 1.0\n",
     "theta1 = 1.0\n",
@@ -252,9 +331,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "def plot_decision_boundary(X, theta0, theta1, ax=None):\n",
     "    if ax is None:\n",
@@ -266,7 +356,7 @@
     "    ax.set_title(\"Decision Boundary\")\n",
     "    \n",
     "legend_map = {0: 'failed', 1: 'passed'}\n",
-    "ax = sns.scatterplot(X, y, hue=pd.Series(y).map(legend_map))\n",
+    "ax = sns.scatterplot(x=X, y=y, hue=pd.Series(y).map(legend_map))\n",
     "ax.set_xlabel('days spent learning for the ML exam')\n",
     "ax.set_ylabel('if students passed')\n",
     "plot_decision_boundary(X, theta0, theta1, ax)\n",
@@ -300,7 +390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {
     "solution2": "hidden",
     "solution2_first": true
@@ -309,7 +399,7 @@
    "source": [
     "def cost_function(y, y_pred):\n",
     "    # START YOUR CODE\n",
-    "    \n",
+    "    cost = -1.0/y.shape[0] * np.sum(y * np.log(y_pred) + (1 - y) * np.log(1 - y_pred))\n",
     "    \n",
     "    # END YOUR CODE\n",
     "    return cost"
@@ -334,6 +424,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "def cost_function(y, y_pred):\n",
     "    n = y.shape[0]\n",
     "    cost = -(1.0 / n) * np.sum(y * np.log(y_pred) + (1 - y) * np.log(1 - y_pred))\n",
@@ -349,7 +440,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -471,6 +562,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "def fit(X, y, alpha, num_epochs, display_every=10):\n",
     "    theta0 = 0.0\n",
     "    theta1 = np.random.randn()\n",
@@ -635,6 +727,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "y_pred_class = y_pred > 0.5"
    ]
   },
@@ -745,6 +838,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "def predict(X, bias, thetas):\n",
     "    z = bias + np.dot(X, thetas)\n",
     "    y_pred = sigmoid(z)\n",
@@ -796,6 +890,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "def gradient(X, y, bias, thetas):\n",
     "    y_pred = predict(X, bias, thetas)\n",
     "    diff = y_pred - y\n",
@@ -882,6 +977,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "bias_2d, thetas_2d, hist_2d = fit(X_train, y_train, alpha=0.1, num_epochs=10000, display_every=1000)\n",
     "plot_validation_curve(hist_2d[\"cost\"])"
    ]
@@ -977,6 +1073,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "y_pred = predict(X_test, bias_2d, thetas_2d)\n",
     "y_pred = (y_pred > 0.5).astype(int)\n",
     "y_pred"
@@ -1049,6 +1146,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "cm = compute_confusion_matrix(y_test, y_pred)\n",
     "plot_confusion_matrix(cm)"
    ]
@@ -1137,6 +1235,7 @@
    },
    "outputs": [],
    "source": [
+    "\n",
     "accuracy = accuracy_score(cm)\n",
     "f1 = f1_score(cm)\n",
     "\n",
@@ -1161,7 +1260,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,
-- 
GitLab