updated scikit learn notebook

Author: dcavar

notebooks/Scikitlearn_logistic_regression.ipynb

@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -123,7 +123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -152,7 +152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -259,7 +259,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -284,7 +284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -300,7 +300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -334,14 +334,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.9662243326599138 0.03377566734008619\n"
+      "0.6969888901292717 0.3030111098707283\n"
      ]
     }
    ],
@@ -358,7 +358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -375,7 +375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -418,7 +418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -435,7 +435,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -453,7 +453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -480,7 +480,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -502,7 +502,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -529,7 +529,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
@@ -558,7 +558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -578,7 +578,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -587,7 +587,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -601,7 +601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
@@ -622,7 +622,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -641,7 +641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -650,7 +650,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -667,7 +667,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -678,14 +678,15 @@
     "        y_hat = sigmoid( np.dot(w, x) + b )\n",
     "        if y_hat > .5:\n",
     "            y_hat = 1\n",
-    "        else: y_hat = 0\n",
+    "        else:\n",
+    "            y_hat = 0\n",
     "        res.append( (y, y_hat) )\n",
     "    return res"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -694,7 +695,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -703,7 +704,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {