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Clean 2_5_2

This commit is contained in:
cif2cif 2021-02-27 20:51:52 +01:00
parent 23913811df
commit 8925a4a3c1

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@ -74,7 +74,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -124,20 +124,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"data": {
"text/plain": [
"DecisionTreeClassifier(max_depth=3, random_state=1)"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.tree import DecisionTreeClassifier\n",
"import numpy as np\n", "import numpy as np\n",
@ -156,24 +145,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "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"
]
}
],
"source": [ "source": [
"print(\"Prediction \", model.predict(x_train))\n", "print(\"Prediction \", model.predict(x_train))\n",
"print(\"Expected \", y_train)" "print(\"Expected \", y_train)"
@ -188,26 +162,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "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"
]
}
],
"source": [ "source": [
"# Print the \n", "# Print the \n",
"print(\"Predicted probabilities\", model.predict_proba(x_train[:10]))" "print(\"Predicted probabilities\", model.predict_proba(x_train[:10]))"
@ -215,17 +172,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy in training 0.9821428571428571\n"
]
}
],
"source": [ "source": [
"# Evaluate Accuracy in training\n", "# Evaluate Accuracy in training\n",
"\n", "\n",
@ -236,17 +185,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy in testing 0.9210526315789473\n"
]
}
],
"source": [ "source": [
"# Now we evaluate error in testing\n", "# Now we evaluate error in testing\n",
"y_test_pred = model.predict(x_test)\n", "y_test_pred = model.predict(x_test)\n",
@ -268,21 +209,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "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<ipython-input-10-7c2cf6067fce>\u001b[0m in \u001b[0;36m<module>\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'"
]
}
],
"source": [ "source": [
"from IPython.display import Image \n", "from IPython.display import Image \n",
"from six import StringIO\n", "from six import StringIO\n",