From 8925a4a3c19154bc2a1825f53dce30e429cb3dad Mon Sep 17 00:00:00 2001 From: cif2cif Date: Sat, 27 Feb 2021 20:51:52 +0100 Subject: [PATCH] Clean 2_5_2 --- ml1/2_5_2_Decision_Tree_Model.ipynb | 97 ++++------------------------- 1 file changed, 13 insertions(+), 84 deletions(-) diff --git a/ml1/2_5_2_Decision_Tree_Model.ipynb b/ml1/2_5_2_Decision_Tree_Model.ipynb index b0289ff..5fe1708 100644 --- a/ml1/2_5_2_Decision_Tree_Model.ipynb +++ b/ml1/2_5_2_Decision_Tree_Model.ipynb @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -124,20 +124,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DecisionTreeClassifier(max_depth=3, random_state=1)" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from sklearn.tree import DecisionTreeClassifier\n", "import numpy as np\n", @@ -156,24 +145,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Prediction [1 0 1 1 1 0 0 1 0 2 0 0 1 2 0 1 2 2 1 1 0 0 2 0 0 2 1 1 2 2 2 2 0 0 1 1 0\n", - " 1 2 1 2 0 2 0 1 0 2 1 0 2 2 0 0 2 0 0 0 2 2 0 1 0 1 0 1 1 1 1 1 0 1 0 1 2\n", - " 0 0 0 0 2 2 0 1 1 2 1 0 0 2 1 1 0 1 1 0 2 1 2 1 2 0 1 0 0 0 2 1 2 1 2 1 2\n", - " 0]\n", - "Expected [1 0 1 1 1 0 0 1 0 2 0 0 1 2 0 1 2 2 1 1 0 0 2 0 0 2 1 1 2 2 2 2 0 0 1 1 0\n", - " 1 2 1 2 0 2 0 1 0 2 1 0 2 2 0 0 2 0 0 0 2 2 0 1 0 1 0 1 1 1 1 1 0 1 0 1 2\n", - " 0 0 0 0 2 2 0 1 1 2 1 0 0 1 1 1 0 1 1 0 2 2 2 1 2 0 1 0 0 0 2 1 2 1 2 1 2\n", - " 0]\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Prediction \", model.predict(x_train))\n", "print(\"Expected \", y_train)" @@ -188,26 +162,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Predicted probabilities [[0. 0.97368421 0.02631579]\n", - " [1. 0. 0. ]\n", - " [0. 0.97368421 0.02631579]\n", - " [0. 0.97368421 0.02631579]\n", - " [0. 0.97368421 0.02631579]\n", - " [1. 0. 0. ]\n", - " [1. 0. 0. ]\n", - " [0. 0.97368421 0.02631579]\n", - " [1. 0. 0. ]\n", - " [0. 0. 1. ]]\n" - ] - } - ], + "outputs": [], "source": [ "# Print the \n", "print(\"Predicted probabilities\", model.predict_proba(x_train[:10]))" @@ -215,17 +172,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy in training 0.9821428571428571\n" - ] - } - ], + "outputs": [], "source": [ "# Evaluate Accuracy in training\n", "\n", @@ -236,17 +185,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy in testing 0.9210526315789473\n" - ] - } - ], + "outputs": [], "source": [ "# Now we evaluate error in testing\n", "y_test_pred = model.predict(x_test)\n", @@ -268,21 +209,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'pydotplus'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mIPython\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisplay\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0msix\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mpydotplus\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpydot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdot_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pydotplus'" - ] - } - ], + "outputs": [], "source": [ "from IPython.display import Image \n", "from six import StringIO\n",