机器学习_机器学习_源码/资料下载-pudn.com

<html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta charset="utf-8"> <meta name="generator" content="pdf2htmlEX"> <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> <link rel="stylesheet" href="https://static.pudn.com/base/css/base.min.css"> <link rel="stylesheet" href="https://static.pudn.com/base/css/fancy.min.css"> <link rel="stylesheet" href="https://static.pudn.com/prod/directory_preview_static/628f932407732924f780be9b/raw.css"> <script src="https://static.pudn.com/base/js/compatibility.min.js"></script> <script src="https://static.pudn.com/base/js/pdf2htmlEX.min.js"></script> <script> try{ pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({}); }catch(e){} </script> <title></title> </head> <body> <div id="sidebar" style="display: none"> <div id="outline"> </div> </div> <div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/628f932407732924f780be9b/bg1.jpg"><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">#<span class="ff2">多层感知器</span></div><div class="t m0 x1 h3 y2 ff1 fs0 fc0 sc0 ls0 ws0">if<span class="_ _0"> </span>("package:h2o"<span class="_ _0"> </span>%in%<span class="_ _0"> </span>search())<span class="_ _0"> </span>{<span class="_ _0"> </span>detach<span class="_ _1"></span>("package:h2o",<span class="_ _0"> </span>unload=TRUE)<span class="_ _0"> </span>}</div><div class="t m0 x1 h3 y3 ff1 fs0 fc0 sc0 ls0 ws0">if<span class="_ _0"> </span>("h2o"<span class="_ _0"> </span>%in%<span class="_ _0"> </span>rownames(installed.packages()))<span class="_ _0"> </span>{<span class="_ _0"> </span>re<span class="_ _1"></span>move.packages("h2o")<span class="_ _0"> </span>}</div><div class="t m0 x1 h3 y4 ff1 fs0 fc0 sc0 ls0 ws0">pkgs<span class="_ _0"> </span><-<span class="_ _0"> </span>c("RCurl","jsonlite")</div><div class="t m0 x1 h3 y5 ff1 fs0 fc0 sc0 ls0 ws0">for<span class="_ _0"> </span>(pkg<span class="_ _0"> </span>in<span class="_ _0"> </span>pkgs)<span class="_ _0"> </span>{</div><div class="t m0 x2 h3 y6 ff1 fs0 fc0 sc0 ls0 ws0">if<span class="_ _0"> </span>(!<span class="_ _0"> </span>(pkg<span class="_ _0"> </span>%in%<span class="_ _0"> </span>rownames(installed.packages())))<span class="_ _0"> </span>{<span class="_ _0"> </span>i<span class="_ _1"></span>nstall.packages(pkg)<span class="_ _0"> </span>}</div><div class="t m0 x1 h3 y7 ff1 fs0 fc0 sc0 ls0 ws0">}</div><div class="t m0 x1 h3 y8 ff1 fs0 fc0 sc0 ls0 ws0">install.packages("h2o",<span class="_ _2"> </span>type="source",</div><div class="t m0 x1 h3 y9 ff1 fs0 fc0 sc0 ls0 ws0">repos=(c("http://h2o-release.s3.amaz<span class="_ _1"></span>onaws.com/h2o/latest_stable_R")))</div><div class="t m0 x1 h3 ya ff1 fs0 fc0 sc0 ls0 ws0">require(h2o)</div><div class="t m0 x1 h3 yb ff1 fs0 fc0 sc0 ls0 ws0">Sys.setenv(JAVA_HOME="C:/Users/86<span class="_ _1"></span>171/Documents/jdk-17.0.2/")</div><div class="t m0 x1 h3 yc ff1 fs0 fc0 sc0 ls0 ws0">h2o.init()</div><div class="t m0 x1 h3 yd ff1 fs0 fc0 sc0 ls0 ws0">h2o.no_progress()</div><div class="t m0 x1 h3 ye ff1 fs0 fc0 sc0 ls0 ws0">h2o.init(min_mem_size='5G',<span class="_ _0"> </span>max_mem_size='1<span class="_ _1"></span>00G')</div><div class="t m0 x1 h3 yf ff1 fs0 fc0 sc0 ls0 ws0">getwd()</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">setwd("D:\<span class="ff2">机器学习</span>\<span class="ff2">山东省青少年心理健康数据</span>")</div><div class="t m0 x1 h3 y11 ff1 fs0 fc0 sc0 ls0 ws0">library(Hmisc)</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">occupancy_train<span class="_ _0"> </span><-<span class="_ _0"> </span>spss.get("<span class="ff2">机器</span>.sav",use.value.lab<span class="_ _1"></span>els<span class="_ _0"> </span>=<span class="_ _0"> </span>TRUE)</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">occupancy_test<span class="_ _0"> </span><-<span class="_ _0"> </span>spss.get("<span class="ff2">机器</span>.sav",use.value.lab<span class="_ _1"></span>els<span class="_ _0"> </span>=<span class="_ _0"> </span>TRUE)</div><div class="t m0 x1 h3 y14 ff1 fs0 fc0 sc0 ls0 ws0">colnames(occupancy_train)<span class="_ _0"> </span><-<span class="_ _0"> </span>c(paste0("x",<span class="_ _0"> </span>1:2<span class="_ _1"></span>6),<span class="_ _0"> </span>"y")</div><div class="t m0 x1 h3 y15 ff1 fs0 fc0 sc0 ls0 ws0">colnames(occupancy_test)<span class="_ _0"> </span><-<span class="_ _0"> </span>c(paste0("x",<span class="_ _0"> </span>1<span class="_ _1"></span>:26),<span class="_ _0"> </span>"y")</div><div class="t m0 x1 h3 y16 ff1 fs0 fc0 sc0 ls0 ws0">occupancy_train[,<span class="_ _0"> </span>5:27]<span class="_ _0"> </span><-<span class="_ _0"> </span>lapply(occupan<span class="_ _1"></span>cy_train[,<span class="_ _0"> </span>5:27],<span class="_ _0"> </span>factor)</div><div class="t m0 x1 h3 y17 ff1 fs0 fc0 sc0 ls0 ws0">occupancy_test[,<span class="_ _0"> </span>5:27]<span class="_ _0"> </span><-<span class="_ _0"> </span>lapply(occupan<span class="_ _1"></span>cy_test[,<span class="_ _0"> </span>5:27],<span class="_ _0"> </span>factor)</div><div class="t m0 x1 h3 y18 ff1 fs0 fc0 sc0 ls0 ws0">x=c("x1","x2","x3","x4","x5","x6","x7","x8","x<span class="_ _1"></span>9","x10","x11","x1<span class="_ _1"></span>2",</div><div class="t m0 x1 h3 y19 ff1 fs0 fc0 sc0 ls0 ws0">"x13","x14","x15","x16<span class="_ _1"></span>","x18","x19","x20","x17","x21","x2<span class="_ _1"></span>2","x23","x24","x25","x26</div><div class="t m0 x1 h3 y1a ff1 fs0 fc0 sc0 ls0 ws0">")</div><div class="t m0 x1 h3 y1b ff1 fs0 fc0 sc0 ls0 ws0">y="y"</div><div class="t m0 x1 h3 y1c ff1 fs0 fc0 sc0 ls0 ws0">occupancy_train.hex<span class="_ _0"> </span><-<span class="_ _0"> </span>as.h2o(x=occupancy_tr<span class="_ _1"></span>ain,</div><div class="t m0 x3 h3 y1d ff1 fs0 fc0 sc0 ls0 ws0">destination_frame<span class="_ _0"> </span>=<span class="_ _0"> </span>"occupancy_train.hex")</div><div class="t m0 x1 h3 y1e ff1 fs0 fc0 sc0 ls0 ws0">occupancy_test.hex<-<span class="_ _0"> </span>as.h2o(x=occupancy_test<span class="_ _1"></span>,</div><div class="t m0 x4 h3 y1f ff1 fs0 fc0 sc0 ls0 ws0">destination_frame<span class="_ _0"> </span>=<span class="_ _0"> </span>"occupancy_test.hex")</div><div class="t m0 x1 h3 y20 ff1 fs0 fc0 sc0 ls0 ws0">occupancy.deepmodel<span class="_ _0"> </span><-<span class="_ _0"> </span>h2o.deeplearning(x=x,</div><div class="t m0 x5 h3 y21 ff1 fs0 fc0 sc0 ls0 ws0">y=y,</div><div class="t m0 x5 h3 y22 ff1 fs0 fc0 sc0 ls0 ws0">training_frame<span class="_ _3"> </span>=</div><div class="t m0 x1 h3 y23 ff1 fs0 fc0 sc0 ls0 ws0">occupancy_train.hex,</div><div class="t m0 x5 h3 y24 ff1 fs0 fc0 sc0 ls0 ws0">validation_frame<span class="_ _4"> </span>=</div><div class="t m0 x1 h3 y25 ff1 fs0 fc0 sc0 ls0 ws0">occupancy_test.hex,</div><div class="t m0 x5 h3 y26 ff1 fs0 fc0 sc0 ls0 ws0">standardize<span class="_ _0"> </span>=<span class="_ _0"> </span>F,</div><div class="t m0 x5 h3 y27 ff1 fs0 fc0 sc0 ls0 ws0">activation<span class="_ _0"> </span>=<span class="_ _0"> </span>"Rectifier",</div><div class="t m0 x5 h3 y28 ff1 fs0 fc0 sc0 ls0 ws0">epochs<span class="_ _0"> </span>=<span class="_ _0"> </span>50,</div><div class="t m0 x5 h3 y29 ff1 fs0 fc0 sc0 ls0 ws0">seed<span class="_ _0"> </span>=<span class="_ _0"> </span>1234567,</div><div class="t m0 x5 h3 y2a ff1 fs0 fc0 sc0 ls0 ws0">hidden<span class="_ _0"> </span>=<span class="_ _0"> </span>5,</div><div class="t m0 x5 h3 y2b ff1 fs0 fc0 sc0 ls0 ws0">variable_importances<span class="_ _0"> </span>=<span class="_ _0"> </span>T,</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div> </body> </html>