R语言H2O最新文档最新版的R语言H2O新增了自动机器学习和xgboost等新功能，分布式多线程算法

文件名称: R语言H2O最新文档

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详细说明：最新版的R语言H2O新增了自动机器学习和xgboost等新功能，分布式多线程算法执行效率较高，值得大家学习！R topics documented h20. EXPORT FILES h20. FRaMes 19 h20, IMPORT 19 h20. JOBS 20 h20. LOGANDECHO 20 h20. MODELS h20. MODEL BUILDERS 21 h20. MODEL METRICS 21 h20. PARSE SETUP h20. RAPIDS 22 h20. REST API VERSION 22 h20. W2V SYNONYMS pkg skip if not develo 22222 3445 apply as character:. H2OFrame 26 as data. frame. H2OFrame 26 as factor as. matrix. H2OFrame 789 as numeric 30 or. H2OFrame 30 australia 31 colnames dim. H2OFrame 32 dimnames H20 Frame 32 generate col ind h2o.ab h2 333 334 h2o. aggregated frame h2o.aggregator ·. 35 h2o.aiC,,,,,, 7 h2o.all 38 h2o.anomaly 38 h2o.any h2o.any Factor h2o. arrange h2o.ascharacter 40 h2o, asfactor h2o.asnumeric ·.· h2o.assign 1122 h2 h2o.auc h2o.autom 44 h2o. betweens h2o. biases 47 R topics do h2o. bottomn 48 h2o. bind o cellin 49 h2o.centers 9 h2o. centers stD h2o. centroid stats h2o.clearLog 51 h2o. cluster 51 h2o. clusterIsUp 52 h2o.cluster Status 52 h2o. cluster sizes 53 h2 h2o.coef norm 54 h2o. colnames 54 h2o.columns by 55 h2o.computeGram 55 h2o. confusion matrix 56 h2o. connect 57 h20.co 58 h20.cos 59 h2o. cosh .60 h20.coxph h2 61 h2o.cross_validationfold_assignment 63 h2o.cross_ validation holdout predictions 64 h2o. cross validation models 64 h2o.cross validation _ predictions 65 h2o.cummax 65 h2o. cummin 66 h2o. cumprod 66 h2o.cumsum 67 h2o. cut 8 h2o.day ofweek h2o.ddp 70 h2 o.decryptionSetup· h2o. deepfeat h2o. deeplearnins h2o.deepwater h2o.deepwater. available h2o.describe ·.· 85 h2o.difflag 1 86 h2o.dim 86 h2o.di h2o.distance h2o. downloadAlllogs 88 h2o.downloads 88 R topics documented h2o. download_mojo h2o.download_pojo oentropy 91 h2o.exp 91 h2o. exportFile 92 h2o.exporthDFS h2o. filIn 93 h2o. filterNACols 94 h2o. findSynonyl 94 h2o. find row by threshold 95 h2o. find threshold by max metric 95 h2o. foor 96 h2o.fi e 96 h2o.gasliFt h2 c ogbl 98 h2o. getAutoML 102 h2o. getConnecti h2o. get Frame 104 h2o.getFuture Model 104 h2o. getGLMFullRegularizationPath 105 h2o. getGrid 5 h2o.geld 106 h2o.get model l06 h2o. getModelTree 107 h2o. getTimezone 108 h2o.get'lypes 108 h2o. get version 108 h2o.gini Coef 109 h2o.glm l10 h2 Og 114 h2o.grep 117 h2o. grid 118 h2o.group b ,,,,,,,,119 b 120 121 h2o.hist ...,,,122 h2o.hit ratio table .123 h2o. hour l23 h2o.ife 124 h2o.import File ..125 h2o. import sql select 127 h2o. 1mp ort_sql_table 128 h2 o impute·· 129 h2o.init 130 h2o.insert Missing values 132 h2o.interaction 133 h2oisax 135 h2o.ischaracter 136 R topics do h2o.isfactor 136 h2oisnumeric 137 h2oisolation Forest 137 h2ois client ..139 h2o. fold column 139 h2o. killMinus3 139 h2 h2o. kurtosis 142 h2o.level 142 h2o.list Timezones 143 h2o.list all extensions 143 h2o.list_api_extensions h2o.list core extensions 144 h2oload Model 144 h2o.lo 145 145 holog 146 h2olog andecho .147 h2o.logloss 147 h2oIs ..148 2o. Istrip 148 h2 150 h2o.make metrics 150 h2o. match 151 h2o.max 152 h20. mean h2o. mean_per_class h2o, mean residual deviance 154 h2o. median 155 h2o. merge l56 h2o. metric ·. h2o. min 158 h2o. mktime 159 h2o.mojo_predict_csv 159 h2o. mojo predict d h2o. month 161 h2o. mse ..162 h2 B 163 h2o. names ·.· ..,..166 h2o. na omit 166 h2o. nchar 167 h2 167 h2o. networkTest 168 h2o.levels l68 h2o.no progress 168 R topics documented h2o.nrow h2o.null deviance h2o.null dof ..170 h20. num iterations 170 h2o.num valid substrings l71 h2o 171 h2o R 172 h2o. parseSetup 173 h2o. partialPlot 174 h2o. performance ..,,,175 h2 O pIve 177 h2o. prcomp 177 h2o.predict_ json 179 h2o. print l80 h2 c O- pi d h2o.pr auc l82 h2o.quantile 184 h2o. random forest 185 h2o.range ..189 h2o. rank_ within_group_by 189 h2o. rbind 19I h2o. relevel 193 h2o. removeall 194 h2o.remove Vecs 194 h2 195 h2o. residual deviance 195 h2o.residual dof 196 h2o.rm 196 h2o.rmse 197 hhh 8 20round 198 t ri h2o. runif 200 h2 Mode 200 h2o. save modeldetails 20l hhh Mo o saveLoY ) oscale 203 2o. scorehisto 203 h2o.sd 204 20. sde 204 hhhh 20. setlevels 205 progress 206 h2o. shutdown 206 h2o.signif 207 R topics do h2o.sin h2o. skewness 208 h2o.splitFrame 209 h2o.sgrt 210 h2o. stackedEnsemble 210 h2o. startLogging 2 h2o. std coef plot 212 h2o. stopLogging h2o.str 214 h2o. stringdist ..214 h2o.strsplit 215 h2o. sub Osubstring h2o.sum 217 h2 c 8 h2o.svd 219 h2o. table 220 h2o, tabulate 221 h2o. tan ..222 222 h2o.target_encode_app h2o. target encode create h2o. toFrame ) h2 o tokenize 226 h2o. tolower ) 7 h2o. topN 227 h2o. toss h2o, tot withinss 228 h2o. toupper 229 h2o, transform h2o. t h2o. trunc 231 h2o. unique ·. 231 h2o.var 232 h2o. varimp 233 h2o. varimp_plot 233 h2o. week h2o. weights h2o. which ) h2o. which max 236 h2o, which min 236 h2o. withins 237 h2o. word2vec 237 h2o.xgboost 238 h2o.xgboost availabl 242 h2 243 H2OAutoML-class 243 H2OClustering Model-class 244 R topics documented H2OConnection-class ....244 H2OConnection Mutablestate 245 H2OCoX PHModel-class 246 H2OCoX PHModelSummary-class 247 H2 OFrame-class· H2O Frame-Extract 248 H2OGrid-class 2 H2OLeafNode-class 249 H20 Model-class H2OModelFuture-class 250 H2OModelMetrics-class ) H2ONode-class H2OSplitNode-class H20Tree-class 253 housevotes 254 54 is character is h2o 1s. numeric 256 length. H2OTree-metho logIcal-or .,257 Modelaccessors 257 names.H20Frame 258 Ops. H20Frame plot. H2OModel 260 olot. H2OTabulate predict. H2OAutoMI 262 predict. H2OModel predict_leaf_node_assignment. H20Model 264 t. H2OFr print. H2OTable 265 range. H2OFrame 266 a. H20Model 267 str coframe 268 summary. H20CoX PHModel-method 268 summary. H20Grid-method 269 summary, H2OModel-method 269 270 walking && Index 273 10 h20-package h2o-package H20R Interface Description This is a package for running H20 via its REST API from within R. To communicate with a H20 instance, the version of the r package must match the version of h20. When connecting to a new H20 cluster, it is necessary to re-run the initializer Details Package: h2o Type ackage Version: 3.22. 1.1 B re-xu Date Fri Dec2814:07:25UTC2018 License: Apache license(==2.0) Depends: R(>=2.13.0), RCurl, jsonlite, statmod, tools, methods, utils This package allows the user to run basic H20 commands using R commands. In order to use it, you must first have H20 running. To run H20 on your local machine, call h2o init without any arguments, and h2o will be automatically launched at localhost: 54321, where the IP is 127.0.0.1 and the port is 54321. If H20 is running on a cluster, you must provide the ip and port of the remote machine as arguments to the h2o init( call H20 supports a number of standard statistical models, such as Glm, K-means, and Random Forest For example, to run GLM, call h2o glm with the H20 parsed data and parameters(response vari- able, error distribution, etc. as arguments. (The operation will be done on the server associated with the data object where H20 is running, not within the R environment) Note that no actual data is stored in the r workspace; and no actual work is carried out by r. r only saves the named objects, which uniquely identify the data set, model, etc on the server. When the user makes a request, R queries the server via the rEst aPl, which returns a son file with the relevant information that r then displays in the console If you are using an older version of H20, use the following porting guide to update your scripts Porting Scripts Author(s) Maintainer: The heo, ai team References ·H2o. ai Homepage ·H2 O Documentation ·H2 O on github

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