| h2o |
H2O R Interface |
| h2o.abs |
Compute the absolute value of x |
| h2o.accuracy |
H2O Model Metric Accessor Functions |
| h2o.acos |
Compute the arc cosine of x |
| h2o.aic |
Retrieve the AIC. If "train", "valid", and "xval" parameters are FALSE (default), then the training AIC value is returned. If more than one parameter is set to TRUE, then a named vector of AICs are returned, where the names are "train", "valid" or "xval". |
| h2o.all |
Given a set of logical vectors, are all of the values true? |
| 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.anyFactor |
Check H2OFrame columns for factors |
| h2o.arrange |
Sorts H2OFrame by the columns specified. Returns a new H2OFrame, like dplyr::arrange. |
| h2o.ascharacter |
Convert H2O Data to Characters |
| h2o.asfactor |
Convert H2O Data to Factors |
| h2o.asnumeric |
Convert H2O Data to Numerics |
| h2o.assign |
Rename an H2O object. |
| h2o.as_date |
Functions to convert between character representations and objects of class "Date" representing calendar dates. |
| h2o.auc |
Retrieve the AUC |
| h2o.betweenss |
Get the between cluster sum of squares. If "train", "valid", and "xval" parameters are FALSE (default), then the training betweenss value is returned. If more than one parameter is set to TRUE, then a named vector of betweenss' are returned, where the names are "train", "valid" or "xval". |
| h2o.biases |
Return the respective bias vector |
| h2o.cbind |
Combine H2O Datasets by Columns |
| h2o.ceiling |
ceiling takes a single numeric argument x and returns a numeric vector containing the smallest integers not less than the corresponding elements of x. |
| h2o.centers |
Retrieve the Model Centers |
| h2o.centersSTD |
Retrieve the Model Centers STD |
| h2o.centroid_stats |
Retrieve the centroid statistics If "train", "valid", and "xval" parameters are FALSE (default), then the training centroid stats value is returned. If more than one parameter is set to TRUE, then a named list of centroid stats data frames are returned, where the names are "train", "valid" or "xval". |
| h2o.clearLog |
Delete All H2O R Logs |
| h2o.clusterInfo |
Print H2O cluster info |
| h2o.clusterIsUp |
Determine if an H2O cluster is up or not |
| h2o.clusterStatus |
Return the status of the cluster |
| h2o.cluster_sizes |
Retrieve the cluster sizes If "train", "valid", and "xval" parameters are FALSE (default), then the training cluster sizes value is returned. If more than one parameter is set to TRUE, then a named list of cluster size vectors are returned, where the names are "train", "valid" or "xval". |
| h2o.coef |
Retrieve the model coefficeints |
| h2o.coef_norm |
Retrieve the normalized coefficients |
| h2o.colnames |
Return column names of an H2OFrame |
| h2o.columns_by_type |
Obtain a list of columns that are specified by 'coltype' |
| h2o.computeGram |
Compute weighted gram matrix. |
| h2o.confusionMatrix |
Access H2O Confusion Matrices |
| h2o.confusionMatrix-method |
Access H2O Confusion Matrices |
| h2o.connect |
Connect to a running H2O instance. |
| h2o.cor |
Correlation of columns. |
| h2o.cos |
Compute the cosine of x |
| h2o.cosh |
Compute the hyperbolic cosine of x |
| h2o.createFrame |
Data H2OFrame Creation in H2O |
| h2o.cross_validation_fold_assignment |
Retrieve the cross-validation fold assignment |
| h2o.cross_validation_holdout_predictions |
Retrieve the cross-validation holdout predictions |
| h2o.cross_validation_models |
Retrieve the cross-validation models |
| h2o.cross_validation_predictions |
Retrieve the cross-validation predictions |
| h2o.cummax |
Return the cumulative max over a column or across a row |
| h2o.cummin |
Return the cumulative min over a column or across a row |
| h2o.cumprod |
Return the cumulative product over a column or across a row |
| h2o.cumsum |
Return the cumulative sum over a column or across a row |
| h2o.cut |
Cut H2O Numeric Data to Factor |
| h2o.day |
Convert Milliseconds to Day of Month in H2O Datasets |
| h2o.dayOfWeek |
Convert Milliseconds to Day of Week in H2O Datasets |
| h2o.dct |
Compute DCT of an H2OFrame |
| h2o.ddply |
Split H2O Dataset, Apply Function, and Return Results |
| h2o.deepfeatures |
Feature Generation via H2O Deep Learning Model |
| h2o.deeplearning |
Build a Deep Neural Network model using CPUs Builds a feed-forward multilayer artificial neural network on an H2OFrame |
| h2o.deepwater |
Build a Deep Learning model using multiple native GPU backends Builds a deep neural network on an H2OFrame containing various data sources |
| h2o.deepwater.available |
Ask the H2O server whether a Deep Water model can be built (depends on availability of native backends) Returns True if a deep water model can be built, or False otherwise. |
| h2o.describe |
H2O Description of A Dataset |
| h2o.difflag1 |
Conduct a lag 1 transform on a numeric H2OFrame column |
| h2o.dim |
Returns the number of rows and columns for an H2OFrame object. |
| h2o.dimnames |
Column names of an H2OFrame |
| h2o.downloadAllLogs |
Download H2O Log Files to Disk |
| h2o.downloadCSV |
Download H2O Data to Disk |
| h2o.download_mojo |
Download the model in MOJO format. |
| h2o.download_pojo |
Download the Scoring POJO (Plain Old Java Object) of an H2O Model |
| h2o.entropy |
Shannon entropy |
| h2o.error |
H2O Model Metric Accessor Functions |
| h2o.exp |
Compute the exponential function of x |
| h2o.exportFile |
Export an H2O Data Frame (H2OFrame) to a File or to a collection of Files. |
| h2o.exportHDFS |
Export a Model to HDFS |
| h2o.F0point5 |
H2O Model Metric Accessor Functions |
| h2o.F1 |
H2O Model Metric Accessor Functions |
| h2o.F2 |
H2O Model Metric Accessor Functions |
| h2o.fallout |
H2O Model Metric Accessor Functions |
| h2o.filterNACols |
Filter NA Columns |
| h2o.findSynonyms |
Find synonyms using a word2vec model. |
| h2o.find_row_by_threshold |
Find the threshold, give the max metric. No duplicate thresholds allowed |
| h2o.find_threshold_by_max_metric |
Find the threshold, give the max metric |
| h2o.floor |
floor takes a single numeric argument x and returns a numeric vector containing the largest integers not greater than the corresponding elements of x. |
| h2o.fnr |
H2O Model Metric Accessor Functions |
| h2o.fpr |
H2O Model Metric Accessor Functions |
| h2o.gainsLift |
Access H2O Gains/Lift Tables |
| h2o.gainsLift-method |
Access H2O Gains/Lift Tables |
| h2o.gbm |
Builds gradient boosted classification trees and gradient boosted regression trees on a parsed data set. |
| h2o.getConnection |
Retrieve an H2O Connection |
| h2o.getFrame |
Get an R Reference to an H2O Dataset, that will NOT be GC'd by default |
| h2o.getFutureModel |
Get future model |
| h2o.getGLMFullRegularizationPath |
Extract full regularization path from glm model (assuming it was run with lambda search option) |
| h2o.getGrid |
Get a grid object from H2O distributed K/V store. |
| h2o.getId |
Get back-end distributed key/value store id from an H2OFrame. |
| h2o.getModel |
Get an R reference to an H2O model |
| h2o.getTimezone |
Get the Time Zone on the H2O Cloud Returns a string |
| h2o.getTypes |
Get the types-per-column |
| h2o.getVersion |
Get h2o version |
| h2o.giniCoef |
Retrieve the GINI Coefficcient |
| h2o.glm |
Fits a generalized linear model, specified by a response variable, a set of predictors, and a description of the error distribution. |
| h2o.glrm |
Generalized low rank decomposition of an H2O data frame. |
| h2o.grep |
Searches for matches to argument 'pattern' within each element of a string column. |
| h2o.grid |
H2O Grid Support |
| h2o.group_by |
Group and Apply by Column |
| h2o.gsub |
String Global Substitute |
| h2o.head |
Return the Head or Tail of an H2O Dataset. |
| h2o.hist |
Compute A Histogram |
| h2o.hit_ratio_table |
Retrieve the Hit Ratios If "train", "valid", and "xval" parameters are FALSE (default), then the training Hit Ratios value is returned. If more than one parameter is set to TRUE, then a named list of Hit Ratio tables are returned, where the names are "train", "valid" or "xval". |
| h2o.hour |
Convert Milliseconds to Hour of Day in H2O Datasets |
| h2o.ifelse |
H2O Apply Conditional Statement |
| h2o.importFile |
Import Files into H2O |
| h2o.importFolder |
Import Files into H2O |
| h2o.importHDFS |
Import Files into H2O |
| h2o.importURL |
Import Files into H2O |
| h2o.import_sql_select |
Import SQL table that is result of SELECT SQL query into H2O |
| h2o.import_sql_table |
Import SQL Table into H2O |
| h2o.impute |
Basic Imputation of H2O Vectors |
| h2o.init |
Initialize and Connect to H2O |
| h2o.insertMissingValues |
Insert Missing Values into an H2OFrame |
| h2o.interaction |
Categorical Interaction Feature Creation in H2O |
| h2o.isax |
iSAX |
| h2o.ischaracter |
Check if character |
| h2o.isfactor |
Check if factor |
| h2o.isnumeric |
Check if numeric |
| h2o.is_client |
Check Client Mode Connection |
| h2o.kfold_column |
Produce a k-fold column vector. |
| h2o.killMinus3 |
Dump the stack into the JVM's stdout. |
| h2o.kmeans |
Performs k-means clustering on an H2O dataset. |
| h2o.kurtosis |
Kurtosis of a column |
| h2o.length |
S3 Group Generic Functions for H2O |
| h2o.levels |
Return the levels from the column requested column. |
| h2o.listTimezones |
List all of the Time Zones Acceptable by the H2O Cloud. |
| h2o.loadModel |
Load H2O Model from HDFS or Local Disk |
| h2o.log |
Compute the logarithm of x |
| h2o.log10 |
Compute the log10 of x |
| h2o.log1p |
Compute the log1p of x |
| h2o.log2 |
Compute the log2 of x |
| h2o.logAndEcho |
Log a message on the server-side logs |
| h2o.logloss |
Retrieve the Log Loss Value |
| h2o.ls |
List Keys on an H2O Cluster |
| h2o.lstrip |
Strip set from left |
| h2o.mae |
Retrieve the Mean Absolute Error Value |
| h2o.makeGLMModel |
Set betas of an existing H2O GLM Model |
| h2o.make_metrics |
Create Model Metrics from predicted and actual values in H2O |
| h2o.match |
Value Matching in H2O |
| h2o.max |
Returns the maxima of the input values. |
| h2o.maxPerClassError |
H2O Model Metric Accessor Functions |
| h2o.mcc |
H2O Model Metric Accessor Functions |
| h2o.mean |
Compute the frame's mean by-column (or by-row). |
| h2o.mean_per_class_accuracy |
H2O Model Metric Accessor Functions |
| h2o.mean_per_class_error |
Retrieve the mean per class error |
| h2o.mean_residual_deviance |
Retrieve the Mean Residual Deviance value |
| h2o.median |
H2O Median |
| h2o.merge |
Merge Two H2O Data Frames |
| h2o.metric |
H2O Model Metric Accessor Functions |
| h2o.min |
Returns the minima of the input values. |
| h2o.missrate |
H2O Model Metric Accessor Functions |
| h2o.mktime |
Compute msec since the Unix Epoch |
| h2o.month |
Convert Milliseconds to Months in H2O Datasets |
| h2o.mse |
Retrieves Mean Squared Error Value |
| h2o.nacnt |
Count of NAs per column |
| h2o.naiveBayes |
Compute naive Bayes probabilities on an H2O dataset. |
| h2o.names |
Column names of an H2OFrame |
| h2o.na_omit |
Remove Rows With NAs |
| h2o.nchar |
String length |
| h2o.ncol |
Return the number of columns present in x. |
| h2o.networkTest |
View Network Traffic Speed |
| h2o.nlevels |
Get the number of factor levels for this frame. |
| h2o.no_progress |
Disable Progress Bar |
| h2o.nrow |
Return the number of rows present in x. |
| h2o.null_deviance |
Retrieve the null deviance If "train", "valid", and "xval" parameters are FALSE (default), then the training null deviance value is returned. If more than one parameter is set to TRUE, then a named vector of null deviances are returned, where the names are "train", "valid" or "xval". |
| h2o.null_dof |
Retrieve the null degrees of freedom If "train", "valid", and "xval" parameters are FALSE (default), then the training null degrees of freedom value is returned. If more than one parameter is set to TRUE, then a named vector of null degrees of freedom are returned, where the names are "train", "valid" or "xval". |
| h2o.num_iterations |
Retrieve the number of iterations. |
| h2o.num_valid_substrings |
Count of substrings >= 2 chars that are contained in file |
| h2o.openLog |
View H2O R Logs |
| h2o.parseRaw |
H2O Data Parsing |
| h2o.parseSetup |
Get a parse setup back for the staged data. |
| h2o.partialPlot |
Partial Dependence Plots |
| h2o.performance |
Model Performance Metrics in H2O |
| h2o.prcomp |
Principal components analysis of an H2O data frame using the power method to calculate the singular value decomposition of the Gram matrix. |
| h2o.precision |
H2O Model Metric Accessor Functions |
| h2o.predict |
Predict on an H2O Model |
| h2o.predict_leaf_node_assignment |
Predict the Leaf Node Assignment on an H2O Model |
| h2o.print |
Print An H2OFrame |
| 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.quantile |
Quantiles of H2O Frames. |
| h2o.r2 |
Retrieve the R2 value |
| h2o.randomForest |
Builds a Random Forest Model on an H2OFrame |
| h2o.range |
Returns a vector containing the minimum and maximum of all the given arguments. |
| h2o.rbind |
Combine H2O Datasets by Rows |
| h2o.recall |
H2O Model Metric Accessor Functions |
| h2o.reconstruct |
Reconstruct Training Data via H2O GLRM Model |
| h2o.relevel |
Reorders levels of an H2O factor, similarly to standard R's relevel. |
| h2o.removeAll |
Remove All Objects on the H2O Cluster |
| h2o.removeVecs |
Delete Columns from an H2OFrame |
| h2o.rep_len |
Replicate Elements of Vectors or Lists into H2O |
| h2o.residual_deviance |
Retrieve the residual deviance If "train", "valid", and "xval" parameters are FALSE (default), then the training residual deviance value is returned. If more than one parameter is set to TRUE, then a named vector of residual deviances are returned, where the names are "train", "valid" or "xval". |
| h2o.residual_dof |
Retrieve the residual degrees of freedom If "train", "valid", and "xval" parameters are FALSE (default), then the training residual degrees of freedom value is returned. If more than one parameter is set to TRUE, then a named vector of residual degrees of freedom are returned, where the names are "train", "valid" or "xval". |
| h2o.rm |
Delete Objects In H2O |
| h2o.rmse |
Retrieves Root Mean Squared Error Value |
| h2o.rmsle |
Retrieve the Root Mean Squared Log Error |
| h2o.round |
Round doubles/floats to the given number of decimal places. |
| h2o.rstrip |
Strip set from right |
| h2o.runif |
Produce a Vector of Random Uniform Numbers |
| h2o.saveModel |
Save an H2O Model Object to Disk |
| h2o.saveModelDetails |
Save an H2O Model Details |
| h2o.saveMojo |
Save an H2O Model Object as Mojo to Disk |
| h2o.scale |
Scaling and Centering of an H2OFrame |
| h2o.scoreHistory |
Retrieve Model Score History |
| h2o.sd |
Standard Deviation of a column of data. |
| h2o.sdev |
Retrieve the standard deviations of principal components |
| h2o.sensitivity |
H2O Model Metric Accessor Functions |
| h2o.setLevels |
Set Levels of H2O Factor Column |
| h2o.setTimezone |
Set the Time Zone on the H2O Cloud |
| h2o.show_progress |
Enable Progress Bar |
| h2o.shutdown |
Shut Down H2O Instance |
| h2o.signif |
Round doubles/floats to the given number of significant digits. |
| h2o.sin |
Compute the sine of x |
| h2o.skewness |
Skewness of a column |
| h2o.specificity |
H2O Model Metric Accessor Functions |
| h2o.splitFrame |
Split an H2O Data Set |
| h2o.sqrt |
Compute the square root of x |
| h2o.stackedEnsemble |
Build a stacked ensemble (aka. Super Learner) using the H2O base learning algorithms specified by the user. |
| h2o.startLogging |
Start Writing H2O R Logs |
| h2o.std_coef_plot |
Plot Standardized Coefficient Magnitudes |
| h2o.stopLogging |
Stop Writing H2O R Logs |
| h2o.str |
Display the structure of an H2OFrame object |
| h2o.strsplit |
String Split |
| h2o.sub |
String Substitute |
| h2o.substr |
Substring |
| h2o.substring |
Substring |
| h2o.sum |
Compute the frame's sum by-column (or by-row). |
| h2o.summary |
Summarizes the columns of an H2OFrame. |
| h2o.svd |
Singular value decomposition of an H2O data frame using the power method. |
| h2o.table |
Cross Tabulation and Table Creation in H2O |
| h2o.tabulate |
Tabulation between Two Columns of an H2OFrame |
| h2o.tail |
Return the Head or Tail of an H2O Dataset. |
| h2o.tan |
Compute the tangent of x |
| h2o.tanh |
Compute the hyperbolic tangent of x |
| h2o.tnr |
H2O Model Metric Accessor Functions |
| h2o.tokenize |
Tokenize String |
| h2o.tolower |
Convert strings to lowercase |
| h2o.totss |
Get the total sum of squares. If "train", "valid", and "xval" parameters are FALSE (default), then the training totss value is returned. If more than one parameter is set to TRUE, then a named vector of totss' are returned, where the names are "train", "valid" or "xval". |
| h2o.tot_withinss |
Get the total within cluster sum of squares. If "train", "valid", and "xval" parameters are FALSE (default), then the training tot_withinss value is returned. If more than one parameter is set to TRUE, then a named vector of tot_withinss' are returned, where the names are "train", "valid" or "xval". |
| h2o.toupper |
Convert strings to uppercase |
| h2o.tpr |
H2O Model Metric Accessor Functions |
| h2o.transform |
Transform words (or sequences of words) to vectors using a word2vec model. |
| h2o.trim |
Trim Space |
| h2o.trunc |
trunc takes a single numeric argument x and returns a numeric vector containing the integers formed by truncating the values in x toward 0. |
| h2o.unique |
H2O Unique |
| h2o.uploadFile |
Import Files into H2O |
| h2o.var |
Variance of a column or covariance of columns. |
| h2o.varimp |
Retrieve the variable importance. |
| h2o.varimp_plot |
Plot Variable Importances |
| h2o.week |
Convert Milliseconds to Week of Week Year in H2O Datasets |
| h2o.weights |
Retrieve the respective weight matrix |
| h2o.which |
Which indices are TRUE? |
| h2o.withinss |
Get the Within SS |
| h2o.word2vec |
Trains a word2vec model on a String column of an H2O data frame. |
| h2o.year |
Convert Milliseconds to Years in H2O Datasets |
| H2OAutoEncoderMetrics-class |
The H2OModelMetrics Object. |
| H2OAutoEncoderModel-class |
The H2OModel object. |
| H2OBinomialMetrics-class |
The H2OModelMetrics Object. |
| H2OBinomialModel-class |
The H2OModel object. |
| H2OClusteringMetrics-class |
The H2OModelMetrics Object. |
| H2OClusteringModel-class |
The H2OClusteringModel object. |
| H2OConnection |
The H2OConnection class. |
| H2OConnection-class |
The H2OConnection class. |
| H2ODimReductionMetrics-class |
The H2OModelMetrics Object. |
| H2ODimReductionModel-class |
The H2OModel object. |
| H2OFrame-Extract |
Extract or Replace Parts of an H2OFrame Object |
| H2OGrid |
H2O Grid |
| H2OGrid-class |
H2O Grid |
| H2OModel |
The H2OModel object. |
| H2OModel-class |
The H2OModel object. |
| H2OModelFuture-class |
H2O Future Model |
| H2OModelMetrics |
The H2OModelMetrics Object. |
| H2OModelMetrics-class |
The H2OModelMetrics Object. |
| H2OMultinomialMetrics-class |
The H2OModelMetrics Object. |
| H2OMultinomialModel-class |
The H2OModel object. |
| H2ORegressionMetrics-class |
The H2OModelMetrics Object. |
| H2ORegressionModel-class |
The H2OModel object. |
| H2OUnknownMetrics-class |
The H2OModelMetrics Object. |
| H2OUnknownModel-class |
The H2OModel object. |
| H2OWordEmbeddingMetrics-class |
The H2OModelMetrics Object. |
| H2OWordEmbeddingModel-class |
The H2OModel object. |
| head.H2OFrame |
Return the Head or Tail of an H2O Dataset. |
| hour |
Convert Milliseconds to Hour of Day in H2O Datasets |
| hour.H2OFrame |
Convert Milliseconds to Hour of Day in H2O Datasets |
| housevotes |
United States Congressional Voting Records 1984 |
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