Update week34.ipynb

This commit is contained in:
Morten Hjorth-Jensen
2021-08-26 08:39:49 +02:00
parent 3ea4269da0
commit e514b736c5
+595 -162
View File
@@ -709,11 +709,8 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
@@ -728,12 +725,18 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"outputs": [],
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0.83685501 -0.85701074 1.64314707 1.00755389 -1.04107604 1.73472194\n",
" 0.02127074 1.27828984 0.52885865 0.09337075]\n"
]
}
],
"source": [
"n = 10\n",
"x = np.random.normal(size=n)\n",
@@ -751,10 +754,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -773,10 +773,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -800,10 +797,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -825,10 +819,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -846,10 +837,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -867,10 +855,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -892,10 +877,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -913,10 +895,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -935,10 +914,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -957,10 +933,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -980,10 +953,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -1003,10 +973,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -1090,10 +1057,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"# Importing various packages\n",
@@ -1116,10 +1080,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
@@ -1161,12 +1122,81 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"outputs": [],
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>First Name</th>\n",
" <th>Last Name</th>\n",
" <th>Place of birth</th>\n",
" <th>Date of Birth T.A.</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Frodo</td>\n",
" <td>Baggins</td>\n",
" <td>Shire</td>\n",
" <td>2968</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Bilbo</td>\n",
" <td>Baggins</td>\n",
" <td>Shire</td>\n",
" <td>2890</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Aragorn II</td>\n",
" <td>Elessar</td>\n",
" <td>Eriador</td>\n",
" <td>2931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Samwise</td>\n",
" <td>Gamgee</td>\n",
" <td>Shire</td>\n",
" <td>2980</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" First Name Last Name Place of birth Date of Birth T.A.\n",
"0 Frodo Baggins Shire 2968\n",
"1 Bilbo Baggins Shire 2890\n",
"2 Aragorn II Elessar Eriador 2931\n",
"3 Samwise Gamgee Shire 2980"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"from IPython.display import display\n",
@@ -1191,12 +1221,81 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"outputs": [],
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>First Name</th>\n",
" <th>Last Name</th>\n",
" <th>Place of birth</th>\n",
" <th>Date of Birth T.A.</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Frodo</th>\n",
" <td>Frodo</td>\n",
" <td>Baggins</td>\n",
" <td>Shire</td>\n",
" <td>2968</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bilbo</th>\n",
" <td>Bilbo</td>\n",
" <td>Baggins</td>\n",
" <td>Shire</td>\n",
" <td>2890</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Aragorn</th>\n",
" <td>Aragorn II</td>\n",
" <td>Elessar</td>\n",
" <td>Eriador</td>\n",
" <td>2931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sam</th>\n",
" <td>Samwise</td>\n",
" <td>Gamgee</td>\n",
" <td>Shire</td>\n",
" <td>2980</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" First Name Last Name Place of birth Date of Birth T.A.\n",
"Frodo Frodo Baggins Shire 2968\n",
"Bilbo Bilbo Baggins Shire 2890\n",
"Aragorn Aragorn II Elessar Eriador 2931\n",
"Sam Samwise Gamgee Shire 2980"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_pandas = pd.DataFrame(data,index=['Frodo','Bilbo','Aragorn','Sam'])\n",
"display(data_pandas)"
@@ -1211,12 +1310,23 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"outputs": [],
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"First Name Aragorn II\n",
"Last Name Elessar\n",
"Place of birth Eriador\n",
"Date of Birth T.A. 2931\n",
"Name: Aragorn, dtype: object"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"display(data_pandas.loc['Aragorn'])"
]
@@ -1230,12 +1340,89 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"outputs": [],
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>First Name</th>\n",
" <th>Last Name</th>\n",
" <th>Place of birth</th>\n",
" <th>Date of Birth T.A.</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Frodo</th>\n",
" <td>Frodo</td>\n",
" <td>Baggins</td>\n",
" <td>Shire</td>\n",
" <td>2968</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bilbo</th>\n",
" <td>Bilbo</td>\n",
" <td>Baggins</td>\n",
" <td>Shire</td>\n",
" <td>2890</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Aragorn</th>\n",
" <td>Aragorn II</td>\n",
" <td>Elessar</td>\n",
" <td>Eriador</td>\n",
" <td>2931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sam</th>\n",
" <td>Samwise</td>\n",
" <td>Gamgee</td>\n",
" <td>Shire</td>\n",
" <td>2980</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pippin</th>\n",
" <td>Peregrin</td>\n",
" <td>Took</td>\n",
" <td>Shire</td>\n",
" <td>2990</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" First Name Last Name Place of birth Date of Birth T.A.\n",
"Frodo Frodo Baggins Shire 2968\n",
"Bilbo Bilbo Baggins Shire 2890\n",
"Aragorn Aragorn II Elessar Eriador 2931\n",
"Sam Samwise Gamgee Shire 2980\n",
"Pippin Peregrin Took Shire 2990"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"new_hobbit = {'First Name': [\"Peregrin\"],\n",
" 'Last Name': [\"Took\"],\n",
@@ -1256,12 +1443,288 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"outputs": [],
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-1.749765</td>\n",
" <td>0.342680</td>\n",
" <td>1.153036</td>\n",
" <td>-0.252436</td>\n",
" <td>0.981321</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.514219</td>\n",
" <td>0.221180</td>\n",
" <td>-1.070043</td>\n",
" <td>-0.189496</td>\n",
" <td>0.255001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>-0.458027</td>\n",
" <td>0.435163</td>\n",
" <td>-0.583595</td>\n",
" <td>0.816847</td>\n",
" <td>0.672721</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-0.104411</td>\n",
" <td>-0.531280</td>\n",
" <td>1.029733</td>\n",
" <td>-0.438136</td>\n",
" <td>-1.118318</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1.618982</td>\n",
" <td>1.541605</td>\n",
" <td>-0.251879</td>\n",
" <td>-0.842436</td>\n",
" <td>0.184519</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.937082</td>\n",
" <td>0.731000</td>\n",
" <td>1.361556</td>\n",
" <td>-0.326238</td>\n",
" <td>0.055676</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.222400</td>\n",
" <td>-1.443217</td>\n",
" <td>-0.756352</td>\n",
" <td>0.816454</td>\n",
" <td>0.750445</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>-0.455947</td>\n",
" <td>1.189622</td>\n",
" <td>-1.690617</td>\n",
" <td>-1.356399</td>\n",
" <td>-1.232435</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>-0.544439</td>\n",
" <td>-0.668172</td>\n",
" <td>0.007315</td>\n",
" <td>-0.612939</td>\n",
" <td>1.299748</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>-1.733096</td>\n",
" <td>-0.983310</td>\n",
" <td>0.357508</td>\n",
" <td>-1.613579</td>\n",
" <td>1.470714</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4\n",
"0 -1.749765 0.342680 1.153036 -0.252436 0.981321\n",
"1 0.514219 0.221180 -1.070043 -0.189496 0.255001\n",
"2 -0.458027 0.435163 -0.583595 0.816847 0.672721\n",
"3 -0.104411 -0.531280 1.029733 -0.438136 -1.118318\n",
"4 1.618982 1.541605 -0.251879 -0.842436 0.184519\n",
"5 0.937082 0.731000 1.361556 -0.326238 0.055676\n",
"6 0.222400 -1.443217 -0.756352 0.816454 0.750445\n",
"7 -0.455947 1.189622 -1.690617 -1.356399 -1.232435\n",
"8 -0.544439 -0.668172 0.007315 -0.612939 1.299748\n",
"9 -1.733096 -0.983310 0.357508 -1.613579 1.470714"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 -0.175300\n",
"1 0.083527\n",
"2 -0.044334\n",
"3 -0.399836\n",
"4 0.331939\n",
"dtype: float64\n",
"0 1.069584\n",
"1 0.965548\n",
"2 1.018232\n",
"3 0.793167\n",
"4 0.918992\n",
"dtype: float64\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3.061679</td>\n",
" <td>0.117430</td>\n",
" <td>1.329492</td>\n",
" <td>0.063724</td>\n",
" <td>0.962990</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.264421</td>\n",
" <td>0.048920</td>\n",
" <td>1.144993</td>\n",
" <td>0.035909</td>\n",
" <td>0.065026</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.209789</td>\n",
" <td>0.189367</td>\n",
" <td>0.340583</td>\n",
" <td>0.667239</td>\n",
" <td>0.452553</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.010902</td>\n",
" <td>0.282259</td>\n",
" <td>1.060349</td>\n",
" <td>0.191963</td>\n",
" <td>1.250636</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2.621102</td>\n",
" <td>2.376547</td>\n",
" <td>0.063443</td>\n",
" <td>0.709698</td>\n",
" <td>0.034047</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.878123</td>\n",
" <td>0.534362</td>\n",
" <td>1.853835</td>\n",
" <td>0.106431</td>\n",
" <td>0.003100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.049462</td>\n",
" <td>2.082875</td>\n",
" <td>0.572069</td>\n",
" <td>0.666597</td>\n",
" <td>0.563167</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.207888</td>\n",
" <td>1.415201</td>\n",
" <td>2.858185</td>\n",
" <td>1.839818</td>\n",
" <td>1.518895</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.296414</td>\n",
" <td>0.446453</td>\n",
" <td>0.000054</td>\n",
" <td>0.375694</td>\n",
" <td>1.689345</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>3.003620</td>\n",
" <td>0.966899</td>\n",
" <td>0.127812</td>\n",
" <td>2.603636</td>\n",
" <td>2.162999</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4\n",
"0 3.061679 0.117430 1.329492 0.063724 0.962990\n",
"1 0.264421 0.048920 1.144993 0.035909 0.065026\n",
"2 0.209789 0.189367 0.340583 0.667239 0.452553\n",
"3 0.010902 0.282259 1.060349 0.191963 1.250636\n",
"4 2.621102 2.376547 0.063443 0.709698 0.034047\n",
"5 0.878123 0.534362 1.853835 0.106431 0.003100\n",
"6 0.049462 2.082875 0.572069 0.666597 0.563167\n",
"7 0.207888 1.415201 2.858185 1.839818 1.518895\n",
"8 0.296414 0.446453 0.000054 0.375694 1.689345\n",
"9 3.003620 0.966899 0.127812 2.603636 2.162999"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
@@ -1288,10 +1751,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"df.columns = ['First', 'Second', 'Third', 'Fourth', 'Fifth']\n",
@@ -1324,10 +1784,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"b = np.arange(16).reshape((4,4))\n",
@@ -1451,10 +1908,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"# Importing various packages\n",
@@ -1583,10 +2037,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -1628,10 +2079,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np \n",
@@ -1801,10 +2249,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
@@ -2008,10 +2453,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"# Common imports\n",
@@ -2059,10 +2501,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"from pylab import plt, mpl\n",
@@ -2095,10 +2534,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"\"\"\" \n",
@@ -2126,10 +2562,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"# Read the experimental data with Pandas\n",
@@ -2171,10 +2604,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"A = Masses['A']\n",
@@ -2196,10 +2626,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"# Now we set up the design matrix X\n",
@@ -2221,10 +2648,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"clf = skl.LinearRegression().fit(X, Energies)\n",
@@ -2242,10 +2666,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"# The mean squared error \n",
@@ -2282,10 +2703,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"\n",
@@ -2333,10 +2751,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"editable": true
},
"metadata": {},
"outputs": [],
"source": [
"from sklearn.neural_network import MLPRegressor\n",
@@ -2388,7 +2803,25 @@
]
}
],
"metadata": {},
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}