{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2-高斯核函数"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"from sklearn import svm\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import scipy.io as sio"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# kernek function 高斯核函数\n",
"def gaussian_kernel(x1, x2, sigma):\n",
" return np.exp(- np.power(x1 - x2, 2).sum() / (2 * (sigma ** 2)))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.32465246735834974"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x1 = np.array([1, 2, 1])\n",
"x2 = np.array([0, 4, -1])\n",
"sigma = 2\n",
"\n",
"gaussian_kernel(x1, x2, sigma)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# load data"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dict_keys(['__header__', '__version__', '__globals__', 'X', 'y'])\n"
]
},
{
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