h2o v3.20.0.8
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R Interface for 'H2O'
R interface for 'H2O', the scalable open source machine learning
platform that offers parallelized implementations of many supervised and
unsupervised machine learning algorithms such as Generalized Linear
Models, Gradient Boosting Machines (including XGBoost), Random Forests,
Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox
Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic
machine learning algorithm (AutoML).
Functions in h2o
| Name | Description | |
| H2OFrame-class | The H2OFrame class | |
| Ops.H2OFrame | S3 Group Generic Functions for H2O | |
| H2OModelMetrics-class | The H2OModelMetrics Object. | |
| H2ONode-class | The H2ONode class. | |
| as.data.frame.H2OFrame | Converts parsed H2O data into an R data frame | |
| as.factor | Convert H2O Data to Factors | |
| H2OConnection-class | The H2OConnection class. | |
| h2o.anomaly | Anomaly Detection via H2O Deep Learning Model | |
| h2o.any | Given a set of logical vectors, is at least one of the values true? | |
| h2o.centers | Retrieve the Model Centers | |
| h2o.centersSTD | Retrieve the Model Centers STD | |
| Logical-or | Logical or for H2OFrames | |
| h2o.coef_norm | Return coefficients fitted on the standardized data (requires standardize = True, which is on by default). These coefficients can be used to evaluate variable importance. | |
| h2o.coef | Return the coefficients that can be applied to the non-standardized data. | |
| h2o.coxph | Trains a Cox Proportional Hazards Model (CoxPH) on an H2O dataset | |
| h2o.createFrame | Data H2OFrame Creation in H2O | |
| h2o.cummax | Return the cumulative max over a column or across a row | |
| ModelAccessors | Accessor Methods for H2OModel Object | |
| as.numeric | Convert H2O Data to Numeric | |
| as.vector.H2OFrame | Convert an H2OFrame to a vector | |
| generate_col_ind | CHeck to see if the column names/indices entered is valid for the dataframe given. This is an internal function | |
| h2o-package | H2O R Interface | |
| h2o.asnumeric | Convert H2O Data to Numerics | |
| h2o.asfactor | Convert H2O Data to Factors | |
| h2o.clusterStatus | Return the status of the cluster | |
| H2OCoxPHModel-class | The H2OCoxPHModel object. | |
| H2OAutoML-class | The H2OAutoML class | |
| H2OSplitNode-class | The H2OSplitNode class. | |
| H2OTree-class | The H2OTree class. | |
| australia | Australia Coastal Data | |
| colnames | Returns the column names of an H2OFrame | |
| h2o.cluster_sizes | Retrieve the cluster sizes | |
| h2o.connect | Connect to a running H2O instance. | |
| dim.H2OFrame | Returns the Dimensions of an H2OFrame | |
| dimnames.H2OFrame | Column names of an H2OFrame | |
| H2OClusteringModel-class | The H2OClusteringModel object. | |
| aaa | Starting H2O For examples | |
| h2o.cummin | Return the cumulative min over a column or across a row | |
| h2o.dim | Returns the number of rows and columns for an H2OFrame object. | |
| H2OGrid-class | H2O Grid | |
| h2o.dimnames | Column names of an H2OFrame | |
| h2o.filterNACols | Filter NA Columns | |
| H2OLeafNode-class | The H2OLeafNode class. | |
| h2o.anyFactor | Check H2OFrame columns for factors | |
| apply | Apply on H2O Datasets | |
| h2o.findSynonyms | Find synonyms using a word2vec model. | |
| h2o.getAutoML | Get an R object that is a subclass of H2OAutoML | |
| as.character.H2OFrame | Convert an H2OFrame to a String | |
| h2o.cor | Correlation of columns. | |
| h2o.getConnection | Retrieve an H2O Connection | |
| as.h2o | Create H2OFrame | |
| && | Logical and for H2OFrames | |
| h2o.ddply | Split H2O Dataset, Apply Function, and Return Results | |
| h2o.decryptionSetup | Setup a Decryption Tool | |
| h2o.getTypes | Get the types-per-column | |
| as.matrix.H2OFrame | Convert an H2OFrame to a matrix | |
| h2o.getVersion | Get h2o version | |
| h2o.aic | Retrieve the Akaike information criterion (AIC) value | |
| h2o.all | Given a set of logical vectors, are all of the values true? | |
| h2o.arrange | Sorts an H2O frame by columns | |
| h2o.automl | Automatic Machine Learning | |
| h2o.aggregated_frame | Retrieve an aggregated frame from an Aggregator model | |
| h2o.assign | Rename an H2O object. | |
| h2o.auc | Retrieve the AUC | |
| h2o.aggregator | Build an Aggregated Frame | |
| h2o.centroid_stats | Retrieve centroid statistics | |
| h2o.biases | Return the respective bias vector | |
| h2o.clearLog | Delete All H2O R Logs | |
| h2o.deepwater | Build a Deep Learning model using multiple native GPU backends | |
| H2OCoxPHModelSummary-class | The H2OCoxPHModelSummary object. | |
| h2o.betweenss | Get the between cluster sum of squares | |
| h2o.computeGram | Compute weighted gram matrix. | |
| h2o.confusionMatrix | Access H2O Confusion Matrices | |
| h2o.cross_validation_models | Retrieve the cross-validation models | |
| h2o.colnames | Return column names of an H2OFrame | |
| h2o.columns_by_type | Obtain a list of columns that are specified by `coltype` | |
| h2o.cross_validation_predictions | Retrieve the cross-validation predictions | |
| H2OFrame-Extract | Extract or Replace Parts of an H2OFrame Object | |
| h2o.bottomN | H2O bottomN | |
| h2o.clusterInfo | Print H2O cluster info | |
| h2o.hist | Compute A Histogram | |
| h2o.deepwater.available | Determines whether Deep Water is available | |
| h2o.cumprod | Return the cumulative product over a column or across a row | |
| h2o.cross_validation_holdout_predictions | Retrieve the cross-validation holdout predictions | |
| h2o.cross_validation_fold_assignment | Retrieve the cross-validation fold assignment | |
| h2o.cut | Cut H2O Numeric Data to Factor | |
| h2o.hit_ratio_table | Retrieve the Hit Ratios | |
| h2o.day | Convert Milliseconds to Day of Month in H2O Datasets | |
| h2o.download_pojo | Download the Scoring POJO (Plain Old Java Object) of an H2O Model | |
| h2o.isax | iSAX | |
| h2o.entropy | Shannon entropy | |
| h2o.cumsum | Return the cumulative sum over a column or across a row | |
| h2o.find_row_by_threshold | Find the threshold, give the max metric. No duplicate thresholds allowed | |
| h2o.ischaracter | Check if character | |
| h2o.find_threshold_by_max_metric | Find the threshold, give the max metric | |
| h2o.deepfeatures | Feature Generation via H2O Deep Learning or DeepWater Model | |
| h2o.distance | Compute a pairwise distance measure between all rows of two numeric H2OFrames. | |
| h2o.floor | Take a single numeric argument and return a numeric vector with the largest integers | |
| h2o.deeplearning | Build a Deep Neural Network model using CPUs | |
| h2o.kmeans | Performs k-means clustering on an H2O dataset | |
| h2o.clusterIsUp | Determine if an H2O cluster is up or not | |
| h2o.flow | Open H2O Flow | |
| H2OModel-class | The H2OModel object. | |
| h2o.giniCoef | Retrieve the GINI Coefficcient | |
| h2o.glrm | Generalized low rank decomposition of an H2O data frame | |
| h2o.grep | Search for matches to an argument pattern | |
| h2o.glm | Fit a generalized linear model | |
| h2o.kurtosis | Kurtosis of a column | |
| H2OModelFuture-class | H2O Future Model | |
| h2o.log1p | Compute the log1p of x | |
| h2o.cos | Compute the cosine of x | |
| h2o.abs | Compute the absolute value of x | |
| h2o.log2 | Compute the log2 of x | |
| h2o.downloadAllLogs | Download H2O Log Files to Disk | |
| h2o.mktime | Compute msec since the Unix Epoch | |
| h2o.cosh | Compute the hyperbolic cosine of x | |
| h2o.mojo_predict_csv | H2O Prediction from R without having H2O running | |
| h2o.describe | H2O Description of A Dataset | |
| h2o.acos | Compute the arc cosine of x | |
| h2o.exp | Compute the exponential function of x | |
| h2o.mean_per_class_error | Retrieve the mean per class error | |
| h2o.difflag1 | Conduct a lag 1 transform on a numeric H2OFrame column | |
| h2o.getModelTree | Fetchces a single tree of a H2O model. This function is intended to be used on Gradient Boosting Machine models or Distributed Random Forest models. | |
| h2o.mean_residual_deviance | Retrieve the Mean Residual Deviance value | |
| h2o.mse | Retrieves Mean Squared Error Value | |
| h2o.randomForest | Build a Random Forest model | |
| h2o.na_omit | Remove Rows With NAs | |
| h2o.as_date | Convert between character representations and objects of Date class | |
| h2o.downloadCSV | Download H2O Data to Disk | |
| h2o.download_mojo | Download the model in MOJO format. | |
| h2o.exportFile | Export an H2O Data Frame (H2OFrame) to a File or to a collection of Files. | |
| h2o.getTimezone | Get the Time Zone on the H2O Cloud Returns a string | |
| h2o.nrow | Return the number of rows present in x. | |
| h2o.range | Returns a vector containing the minimum and maximum of all the given arguments. | |
| h2o.ascharacter | Convert H2O Data to Characters | |
| h2o.gsub | String Global Substitute | |
| h2o.cbind | Combine H2O Datasets by Columns | |
| h2o.init | Initialize and Connect to H2O | |
| h2o.sd | Standard Deviation of a column of data. | |
| h2o.insertMissingValues | Insert Missing Values into an H2OFrame | |
| h2o.ceiling | Take a single numeric argument and return a numeric vector with the smallest integers | |
| h2o.list_all_extensions | List all H2O registered extensions | |
| h2o.list_api_extensions | List registered API extensions | |
| h2o.head | Return the Head or Tail of an H2O Dataset. | |
| h2o.dayOfWeek | Convert Milliseconds to Day of Week in H2O Datasets | |
| h2o.null_deviance | Retrieve the null deviance | |
| h2o.sdev | Retrieve the standard deviations of principal components | |
| h2o.getFrame | Get an R Reference to an H2O Dataset, that will NOT be GC'd by default | |
| h2o.dct | Compute DCT of an H2OFrame | |
| h2o.getFutureModel | Get future model | |
| h2o.pivot | Pivot a frame | |
| h2o.prcomp | Principal component analysis of an H2O data frame | |
| h2o.getGLMFullRegularizationPath | Extract full regularization path from a GLM model | |
| h2o.log | Compute the logarithm of x | |
| h2o.log10 | Compute the log10 of x | |
| h2o.removeAll | Remove All Objects on the H2O Cluster | |
| h2o.exportHDFS | Export a Model to HDFS | |
| h2o.removeVecs | Delete Columns from an H2OFrame | |
| h2o.show_progress | Enable Progress Bar | |
| h2o.fillna | fillNA | |
| h2o.getGrid | Get a grid object from H2O distributed K/V store. | |
| h2o.interaction | Categorical Interaction Feature Creation in H2O | |
| h2o.grid | H2O Grid Support | |
| h2o.scale | Scaling and Centering of an H2OFrame | |
| h2o.group_by | Group and Apply by Column | |
| h2o.make_metrics | Create Model Metrics from predicted and actual values in H2O | |
| h2o.shutdown | Shut Down H2O Instance | |
| h2o.is_client | Check Client Mode Connection | |
| h2o.kfold_column | Produce a k-fold column vector. | |
| h2o.gainsLift | Access H2O Gains/Lift Tables | |
| h2o.match | Value Matching in H2O | |
| h2o.mojo_predict_df | H2O Prediction from R without having H2O running | |
| h2o.gbm | Build gradient boosted classification or regression trees | |
| h2o.month | Convert Milliseconds to Months in H2O Datasets | |
| h2o.scoreHistory | Retrieve Model Score History | |
| h2o.signif | Round doubles/floats to the given number of significant digits. | |
| h2o.sum | Compute the frame's sum by-column (or by-row). | |
| h2o.summary | Summarizes the columns of an H2OFrame. | |
| h2o.names | Column names of an H2OFrame | |
| h2o.sin | Compute the sine of x | |
| h2o.killMinus3 | Dump the stack into the JVM's stdout. | |
| h2o.nchar | String length | |
| h2o.getModel | Get an R reference to an H2O model | |
| h2o.getId | Get back-end distributed key/value store id from an H2OFrame. | |
| h2o.hour | Convert Milliseconds to Hour of Day in H2O Datasets | |
| h2o.totss | Get the total sum of squares. | |
| h2o.ifelse | H2O Apply Conditional Statement | |
| h2o.list_core_extensions | List registered core extensions | |
| h2o.import_sql_table | Import SQL Table into H2O | |
| h2o.loadModel | Load H2O Model from HDFS or Local Disk | |
| h2o.impute | Basic Imputation of H2O Vectors | |
| h2o.max | Returns the maxima of the input values. | |
| h2o.levels | Return the levels from the column requested column. | |
| h2o.ls | List Keys on an H2O Cluster | |
| h2o.num_valid_substrings | Count of substrings >= 2 chars that are contained in file | |
| h2o.listTimezones | List all of the Time Zones Acceptable by the H2O Cloud. | |
| h2o.svd | Singular value decomposition of an H2O data frame using the power method | |
| h2o.table | Cross Tabulation and Table Creation in H2O | |
| h2o.mean | Compute the frame's mean by-column (or by-row). | |
| h2o.import_sql_select | Import SQL table that is result of SELECT SQL query into H2O | |
| h2o.importFile | Import Files into H2O | |
| h2o.openLog | View H2O R Logs | |
| h2o.metric | H2O Model Metric Accessor Functions | |
| h2o.min | Returns the minima of the input values. | |
| h2o.rank_within_group_by | This function will add a new column rank where the ranking is produced as follows: 1. sorts the H2OFrame by columns sorted in by columns specified in group_by_cols and sort_cols in the directions specified by the ascending for the sort_cols. The sort directions for the group_by_cols are ascending only. 2. A new rank column is added to the frame which will contain a rank assignment performed next. The user can choose to assign a name to this new column. The default name is New_Rank_column. 3. For each groupby groups, a rank is assigned to the row starting from 1, 2, ... to the end of that group. 4. If sort_cols_sorted is TRUE, a final sort on the frame will be performed frame according to the sort_cols and the sort directions in ascending. If sort_cols_sorted is FALSE (by default), the frame from step 3 will be returned as is with no extra sort. This may provide a small speedup if desired. | |
| h2o.ncol | Return the number of columns present in x. | |
| h2o.rbind | Combine H2O Datasets by Rows | |
| h2o.topN | H2O topN | |
| h2o.isfactor | Check if factor | |
| h2o.toupper | Convert strings to uppercase | |
| h2o.networkTest | View Network Traffic Speed | |
| h2o.lstrip | Strip set from left | |
| h2o.tot_withinss | Get the total within cluster sum of squares. | |
| h2o.parseRaw | H2O Data Parsing | |
| h2o.mae | Retrieve the Mean Absolute Error Value | |
| h2o.isnumeric | Check if numeric | |
| h2o.residual_dof | Retrieve the residual degrees of freedom | |
| h2o.var | Variance of a column or covariance of columns. | |
| h2o.varimp | Retrieve the variable importance. | |
| h2o.logAndEcho | Log a message on the server-side logs | |
| h2o.withinss | Get the Within SS | |
| h2o.logloss | Retrieve the Log Loss Value | |
| h2o.setLevels | Set Levels of H2O Factor Column | |
| h2o.rm | Delete Objects In H2O | |
| h2o.word2vec | Trains a word2vec model on a String column of an H2O data frame | |
| h2o.setTimezone | Set the Time Zone on the H2O Cloud | |
| h2o.makeGLMModel | Set betas of an existing H2O GLM Model | |
| h2o.sqrt | Compute the square root of x | |
| h2o.which_max | Which indice contains the max value? | |
| h2o.median | H2O Median | |
| h2o.which_min | Which index contains the min value? | |
| h2o.merge | Merge Two H2O Data Frames | |
| h2o.parseSetup | Get a parse setup back for the staged data. | |
| plot.H2OTabulate | Plot an H2O Tabulate Heatmap | |
| names.H2OFrame | Column names of an H2OFrame | |
| predict.H2OAutoML | Predict on an AutoML object | |
| h2o.nlevels | Get the number of factor levels for this frame. | |
| plot.H2OModel | Plot an H2O Model | |
| staged_predict_proba.H2OModel | Predict class probabilities at each stage of an H2O Model | |
| h2o.no_progress | Disable Progress Bar | |
| h2o.nacnt | Count of NAs per column | |
| h2o.prod | Return the product of all the values present in its arguments. | |
| h2o.proj_archetypes | Convert Archetypes to Features from H2O GLRM Model | |
| h2o.stackedEnsemble | Builds a Stacked Ensemble | |
| str.H2OFrame | Display the structure of an H2OFrame object | |
| h2o.sub | String Substitute | |
| h2o.substring | Substring | |
| h2o.partialPlot | Partial Dependence Plots | |
| h2o.target_encode_create | Create Target Encoding Map | |
| h2o.rmse | Retrieves Root Mean Squared Error Value | |
| h2o.toFrame | Convert a word2vec model into an H2OFrame | |
| h2o.varimp_plot | Plot Variable Importances | |
| h2o.rmsle | Retrieve the Root Mean Squared Log Error | |
| h2o.week | Convert Milliseconds to Week of Week Year in H2O Datasets | |
| h2o.xgboost | Build an eXtreme Gradient Boosting model | |
| h2o.performance | Model Performance Metrics in H2O | |
| h2o.relevel | Reorders levels of an H2O factor, similarly to standard R's relevel. | |
| h2o.naiveBayes | Compute naive Bayes probabilities on an H2O dataset. | |
| h2o.reconstruct | Reconstruct Training Data via H2O GLRM Model | |
| h2o.null_dof | Retrieve the null degrees of freedom | |
| h2o.saveModelDetails | Save an H2O Model Details | |
| h2o.saveMojo | Save an H2O Model Object as Mojo to Disk | |
| h2o.xgboost.available | Determines whether an XGBoost model can be built | |
| h2o.skewness | Skewness of a column | |
| is.numeric | Check if numeric | |
| h2o.splitFrame | Split an H2O Data Set | |
| h2o.rep_len | Replicate Elements of Vectors or Lists into H2O | |
| h2o.tokenize | Tokenize String | |
| length,H2OTree-method | Overrides the behavior of length() function on H2OTree class. Returns number of nodes in an H2OTree | |
| h2o.num_iterations | Retrieve the number of iterations. | |
| h2o.tolower | Convert strings to lowercase | |
| h2o.residual_deviance | Retrieve the residual deviance | |
| h2o.weights | Retrieve the respective weight matrix | |
| h2o.predict_json | H2O Prediction from R without having H2O running | |
| h2o.runif | Produce a Vector of Random Uniform Numbers | |
| h2o.std_coef_plot | Plot Standardized Coefficient Magnitudes | |
| h2o.startLogging | Start Writing H2O R Logs | |
| h2o.saveModel | Save an H2O Model Object to Disk | |
| print.H2OFrame | Print An H2OFrame | |
| h2o.stopLogging | Stop Writing H2O R Logs | |
| h2o.print | Print An H2OFrame | |
| h2o.quantile | Quantiles of H2O Frames. | |
| print.H2OTable | Print method for H2OTable objects | |
| summary,H2OModel-method | Print the Model Summary | |
| use.package | Use optional package | |
| h2o.str | Display the structure of an H2OFrame object | |
| h2o.tabulate | Tabulation between Two Columns of an H2OFrame | |
| h2o.which | Which indices are TRUE? | |
| h2o.r2 | Retrieve the R2 value | |
| is.factor | Check if factor | |
| is.h2o | Is H2O Frame object | |
| h2o.tan | Compute the tangent of x | |
| h2o.trunc | Truncate values in x toward 0 | |
| prostate | Prostate Cancer Study | |
| h2o.unique | H2O Unique | |
| predict.H2OModel | Predict on an H2O Model | |
| predict_leaf_node_assignment.H2OModel | Predict the Leaf Node Assignment on an H2O Model | |
| range.H2OFrame | Range of an H2O Column | |
| walking | Muscular Actuations for Walking Subject | |
| zzz | Shutdown H2O cloud after examples run | |
| h2o.round | Round doubles/floats to the given number of decimal places. | |
| h2o.rstrip | Strip set from right | |
| h2o.stringdist | Compute element-wise string distances between two H2OFrames | |
| h2o.strsplit | String Split | |
| h2o.tanh | Compute the hyperbolic tangent of x | |
| h2o.target_encode_apply | Apply Target Encoding Map to Frame | |
| h2o.transform | Transform words (or sequences of words) to vectors using a word2vec model. | |
| h2o.trim | Trim Space | |
| h2o.year | Convert Milliseconds to Years in H2O Datasets | |
| housevotes | United States Congressional Voting Records 1984 | |
| iris | Edgar Anderson's Iris Data | |
| is.character | Check if character | |
| summary,H2OCoxPHModel-method | Summary method for H2OCoxPHModel objects | |
| summary,H2OGrid-method | Format grid object in user-friendly way | |
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Details
| Type | Package |
| Date | 2018-09-21 |
| License | Apache License (== 2.0) |
| URL | https://github.com/h2oai/h2o-3 |
| BugReports | https://0xdata.atlassian.net/projects/PUBDEV |
| NeedsCompilation | no |
| SystemRequirements | Java (>= 7) |
| Collate | 'aggregator.R' 'astfun.R' 'automl.R' 'classes.R' 'config.R' 'connection.R' 'constants.R' 'datasets.R' 'logging.R' 'communication.R' 'kvstore.R' 'frame.R' 'import.R' 'parse.R' 'export.R' 'edicts.R' 'models.R' 'coxph.R' 'coxphutils.R' 'kmeans.R' 'gbm.R' 'glm.R' 'glrm.R' 'pca.R' 'svd.R' 'deeplearning.R' 'stackedensemble.R' 'deepwater.R' 'xgboost.R' 'randomforest.R' 'naivebayes.R' 'word2vec.R' 'w2vutils.R' 'locate.R' 'grid.R' 'predict.R' 'zzz.R' |
| Packaged | 2018-09-21 16:57:08 UTC; jenkins |
| Repository | CRAN |
| Date/Publication | 2018-09-25 10:30:03 UTC |
| suggests | bit64 (>= 0.9.7) , data.table (>= 1.9.8) , ggplot2 , Matrix , mlbench , slam , survival |
| imports | graphics , jsonlite , RCurl , tools , utils |
| depends | methods , R (>= 2.13.0) , stats |
| Contributors | Amy Wang, Spencer Aiello, Tom Kraljevic, Anqi Fu, Yuan Tang, Jan Gorecki, Matt Dowle, Patrick Aboyoun, H2O.ai, Navdeep Gill, Arno Candel, Cliff Click, Tomas Nykodym, Michal Kurka, Michal Malohlava, Ludi Rehak, Eric Eckstrand, Brandon Hill, Sebastian Vidrio, Surekha Jadhawani, Raymond Peck, Wendy Wong, Lauren DiPerna |
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