{"id":4058,"date":"2023-07-13T21:08:59","date_gmt":"2023-07-13T21:08:59","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/"},"modified":"2023-07-13T21:08:59","modified_gmt":"2023-07-13T21:08:59","slug":"%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/","title":{"rendered":"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e scikit-learn"},"content":{"rendered":"

<\/p>\n

\n

\u041f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f<\/a> \u2014 \u044d\u0442\u043e \u043c\u0435\u0442\u043e\u0434, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c, \u043a\u043e\u0433\u0434\u0430 \u0441\u0432\u044f\u0437\u044c \u043c\u0435\u0436\u0434\u0443 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439-\u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u043e\u043c \u0438 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043e\u0442\u0432\u0435\u0442\u0430<\/a> \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043d\u0435\u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439.<\/span><\/p>\n

\u042d\u0442\u043e\u0442 \u0442\u0438\u043f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u043f\u0440\u0438\u043d\u0438\u043c\u0430\u0435\u0442 \u0444\u043e\u0440\u043c\u0443:<\/span><\/p>\n

Y = \u03b2 0<\/sub> +<\/sup> \u03b2 1<\/sub> X + \u03b2 2<\/sub> X 2<\/sup> + \u2026 + \u03b2 h<\/sub><\/span><\/p>\n

\u0433\u0434\u0435 h<\/em> \u2014 \u00ab\u0441\u0442\u0435\u043f\u0435\u043d\u044c\u00bb \u043c\u043d\u043e\u0433\u043e\u0447\u043b\u0435\u043d\u0430.<\/span><\/p>\n

\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u043e\u0448\u0430\u0433\u043e\u0432\u043e\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0432 Python \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e sklearn.<\/span><\/p>\n

\u0428\u0430\u0433 1. \u0421\u043e\u0437\u0434\u0430\u0439\u0442\u0435 \u0434\u0430\u043d\u043d\u044b\u0435<\/strong><\/span><\/h2>\n

\u0421\u043d\u0430\u0447\u0430\u043b\u0430 \u0434\u0430\u0432\u0430\u0439\u0442\u0435 \u0441\u043e\u0437\u0434\u0430\u0434\u0438\u043c \u0434\u0432\u0430 \u043c\u0430\u0441\u0441\u0438\u0432\u0430 NumPy \u0434\u043b\u044f \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u0430 \u0438 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043e\u0442\u0432\u0435\u0442\u0430:<\/span> <\/p>\n

 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nimport<\/span> numpy as<\/span> np\n\n#define predictor and response variables\n<\/span>x = np. array<\/span> ([2, 3, 4, 5, 6, 7, 7, 8, 9, 11, 12])\ny = np. array<\/span> ([18, 16, 15, 17, 20, 23, 25, 28, 31, 30, 29])\n\n#create scatterplot to visualize relationship between x and y\n<\/span>plt. scatter<\/span> (x,y)\n<\/strong><\/pre>\n
\"\"<\/p>\n
 \u0418\u0437 \u0434\u0438\u0430\u0433\u0440\u0430\u043c\u043c\u044b \u0440\u0430\u0441\u0441\u0435\u044f\u043d\u0438\u044f \u043c\u044b \u0432\u0438\u0434\u0438\u043c, \u0447\u0442\u043e \u0441\u0432\u044f\u0437\u044c \u043c\u0435\u0436\u0434\u0443 x \u0438 y \u043d\u0435 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439.<\/span><\/p>\n
 \u041f\u043e\u044d\u0442\u043e\u043c\u0443 \u0445\u043e\u0440\u043e\u0448\u0435\u0439 \u0438\u0434\u0435\u0435\u0439 \u0431\u0443\u0434\u0435\u0442 \u043f\u043e\u0434\u043e\u0433\u043d\u0430\u0442\u044c \u043a \u0434\u0430\u043d\u043d\u044b\u043c \u043c\u043e\u0434\u0435\u043b\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u0447\u0442\u043e\u0431\u044b \u043e\u0442\u0440\u0430\u0437\u0438\u0442\u044c \u043d\u0435\u043b\u0438\u043d\u0435\u0439\u043d\u0443\u044e \u0441\u0432\u044f\u0437\u044c \u043c\u0435\u0436\u0434\u0443 \u0434\u0432\u0443\u043c\u044f \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u043c\u0438.<\/span><\/p>\n
 \u0428\u0430\u0433 2. \u041f\u043e\u0434\u0431\u0435\u0440\u0438\u0442\u0435 \u043c\u043e\u0434\u0435\u043b\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438<\/strong><\/span><\/h2>\n
 \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043a\u043e\u0434\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u0438 sklearn \u0434\u043b\u044f \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438 \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0441\u0442\u0435\u043f\u0435\u043d\u0438 3 \u044d\u0442\u043e\u043c\u0443 \u043d\u0430\u0431\u043e\u0440\u0443 \u0434\u0430\u043d\u043d\u044b\u0445:<\/span><\/p>\n
 from<\/span> sklearn. preprocessing<\/span> import<\/span> PolynomialFeatures\nfrom<\/span> sklearn. linear_model<\/span> import<\/span> LinearRegression\n\n#specify degree of 3 for polynomial regression model\n#include bias=False means don't force y-intercept to equal zero<\/span>\npoly = PolynomialFeatures(degree= 3<\/span> , include_bias= False<\/span> )\n\n#reshape data to work properly with sklearn\n<\/span>poly_features = poly. fit_transform<\/span> ( x.reshape<\/span> (-1, 1))\n\n#fit polynomial regression model\n<\/span>poly_reg_model = LinearRegression()\npoly_reg_model. fit<\/span> (poly_features,y)\n\n#display model coefficients\n<\/span>print<\/span> (poly_reg_model. intercept_<\/span> , poly_reg_model. coef_<\/span> )\n\n33.62640037532282 [-11.83877127 2.25592957 -0.10889554]\n<\/strong><\/span><\/pre>\n
 \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u043a\u043e\u044d\u0444\u0444\u0438\u0446\u0438\u0435\u043d\u0442\u044b \u043c\u043e\u0434\u0435\u043b\u0438, \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043d\u044b\u0435 \u0432 \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0435\u0439 \u0441\u0442\u0440\u043e\u043a\u0435, \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u0437\u0430\u043f\u0438\u0441\u0430\u0442\u044c \u0443\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435 \u043f\u043e\u0434\u043e\u0431\u0440\u0430\u043d\u043d\u043e\u0439 \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c:<\/span><\/p>\n
 \u0443 = -0,109\u0445 3<\/sup> + 2,256\u0445 2<\/sup> \u2013 11,839\u0445 + 33,626<\/span><\/p>\n
 \u042d\u0442\u043e \u0443\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435 \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0434\u043b\u044f \u043d\u0430\u0445\u043e\u0436\u0434\u0435\u043d\u0438\u044f \u043e\u0436\u0438\u0434\u0430\u0435\u043c\u043e\u0433\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043e\u0442\u043a\u043b\u0438\u043a\u0430 \u043f\u0440\u0438 \u0437\u0430\u0434\u0430\u043d\u043d\u043e\u043c \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u043e\u0439 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439.<\/span><\/p>\n
 \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0435\u0441\u043b\u0438 x \u0440\u0430\u0432\u043d\u043e 4, \u043e\u0436\u0438\u0434\u0430\u0435\u043c\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043e\u0442\u0432\u0435\u0442\u0430 y \u0431\u0443\u0434\u0435\u0442 \u0440\u0430\u0432\u043d\u043e 15,39:<\/span><\/p>\n
 \u0443 = -0,109(4) 3<\/sup> + 2,256(4) 2<\/sup> \u2013 11,839(4) + 33,626= 15,39<\/span><\/p>\n
 \u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435<\/strong> . \u0427\u0442\u043e\u0431\u044b \u043f\u043e\u0434\u043e\u0433\u043d\u0430\u0442\u044c \u043c\u043e\u0434\u0435\u043b\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0441 \u0434\u0440\u0443\u0433\u043e\u0439 \u0441\u0442\u0435\u043f\u0435\u043d\u044c\u044e, \u043f\u0440\u043e\u0441\u0442\u043e \u0438\u0437\u043c\u0435\u043d\u0438\u0442\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442\u0430 \u0441\u0442\u0435\u043f\u0435\u043d\u0438<\/strong> \u0432 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 PolynomialFeatures()<\/strong> .<\/span><\/p>\n
 \u0428\u0430\u0433 3. \u0412\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438 \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438<\/span><\/strong><\/h2>\n
 \u041d\u0430\u043a\u043e\u043d\u0435\u0446, \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u0441\u043e\u0437\u0434\u0430\u0442\u044c \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0433\u0440\u0430\u0444\u0438\u043a \u0434\u043b\u044f \u0432\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u043c\u043e\u0434\u0435\u043b\u0438 \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0435\u0439 \u0438\u0441\u0445\u043e\u0434\u043d\u044b\u043c \u0442\u043e\u0447\u043a\u0430\u043c \u0434\u0430\u043d\u043d\u044b\u0445:<\/span><\/span> <\/p>\n
 #use model to make predictions on response variable\n<\/span>y_predicted = poly_reg_model. predict<\/span> (poly_features)\n\n#create scatterplot of x vs. y\n<\/span>plt. scatter<\/span> (x,y)\n\n#add line to show fitted polynomial regression model\n<\/span>plt. plot<\/span> (x,y_predicted,color=' purple<\/span> ')\n<\/strong><\/span><\/pre>\n
\"\"<\/p>\n
 \u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435<\/strong> . \u041f\u043e\u043b\u043d\u0443\u044e \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044e \u043f\u043e \u0444\u0443\u043d\u043a\u0446\u0438\u0438 sklearn PolynomialFeatures()<\/strong> \u043c\u043e\u0436\u043d\u043e \u043d\u0430\u0439\u0442\u0438 \u0437\u0434\u0435\u0441\u044c<\/a> .<\/span><\/p>\n
 \u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0441\u0443\u0440\u0441\u044b<\/span><\/strong><\/span><\/h2>\n
 \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0430\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u0434\u0440\u0443\u0433\u0438\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u043d\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e sklearn:<\/span><\/p>\n
 \u041a\u0430\u043a \u0438\u0437\u0432\u043b\u0435\u0447\u044c \u043a\u043e\u044d\u0444\u0444\u0438\u0446\u0438\u0435\u043d\u0442\u044b \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0438\u0437 sklearn<\/a>
 \u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0441\u0431\u0430\u043b\u0430\u043d\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0443\u044e \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e sklearn<\/a>
 \u041a\u0430\u043a \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043e\u0442\u0447\u0435\u0442 \u043e \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u0432 Sklearn<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u041f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f \u2014 \u044d\u0442\u043e \u043c\u0435\u0442\u043e\u0434, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c, \u043a\u043e\u0433\u0434\u0430 \u0441\u0432\u044f\u0437\u044c \u043c\u0435\u0436\u0434\u0443 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439-\u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u043e\u043c \u0438 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043e\u0442\u0432\u0435\u0442\u0430 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043d\u0435\u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439. \u042d\u0442\u043e\u0442 \u0442\u0438\u043f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u043f\u0440\u0438\u043d\u0438\u043c\u0430\u0435\u0442 \u0444\u043e\u0440\u043c\u0443: Y = \u03b2 0 + \u03b2 1 X + \u03b2 2 X 2 + \u2026 + \u03b2 h \u0433\u0434\u0435 h \u2014 \u00ab\u0441\u0442\u0435\u043f\u0435\u043d\u044c\u00bb \u043c\u043d\u043e\u0433\u043e\u0447\u043b\u0435\u043d\u0430. \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u043e\u0448\u0430\u0433\u043e\u0432\u043e\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-4058","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Scikit-Learn \u2014 Statorials<\/title>\n<meta name=\"description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c sklearn \u0432 Python, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ru\/\u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0430\u044f-\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f-2\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Scikit-Learn \u2014 Statorials\" \/>\n<meta property=\"og:description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c sklearn \u0432 Python, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ru\/\u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0430\u044f-\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f-2\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-13T21:08:59+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/polysk1.png\" \/>\n<meta name=\"author\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e \u0430\u0432\u0442\u043e\u0440\u043e\u043c\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u041f\u0440\u0438\u043c\u0435\u0440\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0434\u043b\u044f \u0447\u0442\u0435\u043d\u0438\u044f\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 \u043c\u0438\u043d\u0443\u0442\u0430\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/\",\"url\":\"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/\",\"name\":\"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Scikit-Learn \u2014 Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ru\/#website\"},\"datePublished\":\"2023-07-13T21:08:59+00:00\",\"dateModified\":\"2023-07-13T21:08:59+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ru\/#\/schema\/person\/774949a85feafc6654ba9cefc39d3cae\"},\"description\":\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c sklearn \u0432 Python, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/#breadcrumb\"},\"inLanguage\":\"ru-RU\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u0414\u043e\u043c\",\"item\":\"https:\/\/statorials.org\/ru\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e scikit-learn\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/ru\/#website\",\"url\":\"https:\/\/statorials.org\/ru\/\",\"name\":\"Statorials\",\"description\":\"\u0412\u0430\u0448 \u043f\u0443\u0442\u0435\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c \u043f\u043e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0433\u0440\u0430\u043c\u043e\u0442\u043d\u043e\u0441\u0442\u0438!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/ru\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"ru-RU\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/ru\/#\/schema\/person\/774949a85feafc6654ba9cefc39d3cae\",\"name\":\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ru-RU\",\"@id\":\"https:\/\/statorials.org\/ru\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/ru\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/ru\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\"},\"description\":\"\u0417\u0434\u0440\u0430\u0432\u0441\u0442\u0432\u0443\u0439\u0442\u0435, \u044f \u0411\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d, \u043f\u0440\u043e\u0444\u0435\u0441\u0441\u043e\u0440 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438 \u043d\u0430 \u043f\u0435\u043d\u0441\u0438\u0438, \u0441\u0442\u0430\u0432\u0448\u0438\u0439 \u043f\u0440\u0435\u0434\u0430\u043d\u043d\u044b\u043c \u043f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u0442\u0435\u043b\u0435\u043c Statorials. \u0418\u043c\u0435\u044f \u043e\u0431\u0448\u0438\u0440\u043d\u044b\u0439 \u043e\u043f\u044b\u0442 \u0438 \u0437\u043d\u0430\u043d\u0438\u044f \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438, \u044f \u0445\u043e\u0447\u0443 \u043f\u043e\u0434\u0435\u043b\u0438\u0442\u044c\u0441\u044f \u0441\u0432\u043e\u0438\u043c\u0438 \u0437\u043d\u0430\u043d\u0438\u044f\u043c\u0438, \u0447\u0442\u043e\u0431\u044b \u0440\u0430\u0441\u0448\u0438\u0440\u0438\u0442\u044c \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0438 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Statorials. \u0423\u0437\u043d\u0430\u0442\u044c \u0431\u043e\u043b\u044c\u0448\u0435\",\"sameAs\":[\"https:\/\/statorials.org\/ru\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Scikit-Learn \u2014 Statorials","description":"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c sklearn \u0432 Python, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/statorials.org\/ru\/\u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0430\u044f-\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f-2\/","og_locale":"ru_RU","og_type":"article","og_title":"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Scikit-Learn \u2014 Statorials","og_description":"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c sklearn \u0432 Python, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.","og_url":"https:\/\/statorials.org\/ru\/\u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0430\u044f-\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f-2\/","og_site_name":"Statorials","article_published_time":"2023-07-13T21:08:59+00:00","og_image":[{"url":"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/polysk1.png"}],"author":"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d","twitter_card":"summary_large_image","twitter_misc":{"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e \u0430\u0432\u0442\u043e\u0440\u043e\u043c":"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d","\u041f\u0440\u0438\u043c\u0435\u0440\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0434\u043b\u044f \u0447\u0442\u0435\u043d\u0438\u044f":"1 \u043c\u0438\u043d\u0443\u0442\u0430"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/","url":"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/","name":"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Scikit-Learn \u2014 Statorials","isPartOf":{"@id":"https:\/\/statorials.org\/ru\/#website"},"datePublished":"2023-07-13T21:08:59+00:00","dateModified":"2023-07-13T21:08:59+00:00","author":{"@id":"https:\/\/statorials.org\/ru\/#\/schema\/person\/774949a85feafc6654ba9cefc39d3cae"},"description":"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c sklearn \u0432 Python, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.","breadcrumb":{"@id":"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/#breadcrumb"},"inLanguage":"ru-RU","potentialAction":[{"@type":"ReadAction","target":["https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/statorials.org\/ru\/%d0%bf%d0%be%d0%bb%d0%b8%d0%bd%d0%be%d0%bc%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%81%d0%b8%d1%8f-2\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u0414\u043e\u043c","item":"https:\/\/statorials.org\/ru\/"},{"@type":"ListItem","position":2,"name":"\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e scikit-learn"}]},{"@type":"WebSite","@id":"https:\/\/statorials.org\/ru\/#website","url":"https:\/\/statorials.org\/ru\/","name":"Statorials","description":"\u0412\u0430\u0448 \u043f\u0443\u0442\u0435\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c \u043f\u043e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0433\u0440\u0430\u043c\u043e\u0442\u043d\u043e\u0441\u0442\u0438!","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/statorials.org\/ru\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"ru-RU"},{"@type":"Person","@id":"https:\/\/statorials.org\/ru\/#\/schema\/person\/774949a85feafc6654ba9cefc39d3cae","name":"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d","image":{"@type":"ImageObject","inLanguage":"ru-RU","@id":"https:\/\/statorials.org\/ru\/#\/schema\/person\/image\/","url":"https:\/\/statorials.org\/ru\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","contentUrl":"https:\/\/statorials.org\/ru\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","caption":"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d"},"description":"\u0417\u0434\u0440\u0430\u0432\u0441\u0442\u0432\u0443\u0439\u0442\u0435, \u044f \u0411\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d, \u043f\u0440\u043e\u0444\u0435\u0441\u0441\u043e\u0440 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438 \u043d\u0430 \u043f\u0435\u043d\u0441\u0438\u0438, \u0441\u0442\u0430\u0432\u0448\u0438\u0439 \u043f\u0440\u0435\u0434\u0430\u043d\u043d\u044b\u043c \u043f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u0442\u0435\u043b\u0435\u043c Statorials. \u0418\u043c\u0435\u044f \u043e\u0431\u0448\u0438\u0440\u043d\u044b\u0439 \u043e\u043f\u044b\u0442 \u0438 \u0437\u043d\u0430\u043d\u0438\u044f \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438, \u044f \u0445\u043e\u0447\u0443 \u043f\u043e\u0434\u0435\u043b\u0438\u0442\u044c\u0441\u044f \u0441\u0432\u043e\u0438\u043c\u0438 \u0437\u043d\u0430\u043d\u0438\u044f\u043c\u0438, \u0447\u0442\u043e\u0431\u044b \u0440\u0430\u0441\u0448\u0438\u0440\u0438\u0442\u044c \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0438 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e Statorials. \u0423\u0437\u043d\u0430\u0442\u044c \u0431\u043e\u043b\u044c\u0448\u0435","sameAs":["https:\/\/statorials.org\/ru"]}]}},"yoast_meta":{"yoast_wpseo_title":"","yoast_wpseo_metadesc":"","yoast_wpseo_canonical":""},"_links":{"self":[{"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/posts\/4058","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/comments?post=4058"}],"version-history":[{"count":0,"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/posts\/4058\/revisions"}],"wp:attachment":[{"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/media?parent=4058"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/categories?post=4058"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statorials.org\/ru\/wp-json\/wp\/v2\/tags?post=4058"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
 \u0418\u0437 \u0433\u0440\u0430\u0444\u0438\u043a\u0430 \u043c\u044b \u0432\u0438\u0434\u0438\u043c, \u0447\u0442\u043e \u043c\u043e\u0434\u0435\u043b\u044c \u043f\u043e\u043b\u0438\u043d\u043e\u043c\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u043f\u043e\u0445\u043e\u0436\u0435, \u0445\u043e\u0440\u043e\u0448\u043e \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u0435\u0442 \u0434\u0430\u043d\u043d\u044b\u043c \u0431\u0435\u0437 \u043f\u0435\u0440\u0435\u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f<\/a> .<\/span><\/p>\n