h2o v3.28.0.2
0
Monthly downloads
R Interface for the 'H2O' Scalable Machine Learning Platform
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-Extract | Extract or Replace Parts of an H2OFrame Object | |
| Ops.H2OFrame | S3 Group Generic Functions for H2O | |
| H2ONode-class | The H2ONode class. | |
| .h2o.doRawPOST | Perform a low-level HTTP POST operation on an H2O instance | |
| H2OSplitNode-class | The H2OSplitNode class. | |
| as.h2o | Create H2OFrame | |
| H2OGrid-class | H2O Grid | |
| .h2o.__ALL_CAPABILITIES | Capabilities endpoints | |
| H2OModel-class | The H2OModel object. | |
| as.data.frame.H2OFrame | Converts parsed H2O data into an R data frame | |
| H2OLeafNode-class | The H2OLeafNode class. | |
| H2OFrame-class | The H2OFrame class | |
| h2o.getConnection | Retrieve an H2O Connection | |
| as.factor | Convert H2O Data to Factors | |
| .h2o.locate | Locate a file given the pattern <bucket>/<path/to/file> e.g. h2o:::.h2o.locate("smalldata/iris/iris22.csv") returns the absolute path to iris22.csv | |
| .h2o.__MODEL_METRICS | Model Metrics Endpoint | |
| dimnames.H2OFrame | Column names of an H2OFrame | |
| as.matrix.H2OFrame | Convert an H2OFrame to a matrix | |
| .h2o.__MODEL_BUILDERS | Model Builder Endpoint Generator | |
| dim.H2OFrame | Returns the Dimensions of an H2OFrame | |
| .h2o.__CREATE_FRAME | H2OFrame Manipulation | |
| .h2o.doSafePOST | Perform a safe (i.e. error-checked) HTTP POST request to an H2O cluster. | |
| .h2o.__JOBS | Administrative Endpoints | |
| H2OCoxPHModel-class | The H2OCoxPHModel object. | |
| .h2o.__DECRYPTION_SETUP | Decryption Endpoints | |
| h2o.any | Given a set of logical vectors, is at least one of the values true? | |
| h2o.anomaly | Anomaly Detection via H2O Deep Learning Model | |
| .h2o.doSafeGET | Perform a safe (i.e. error-checked) HTTP GET request to an H2O cluster. | |
| h2o.deepfeatures | Feature Generation via H2O Deep Learning or DeepWater Model | |
| h2o.colnames | Return column names of an H2OFrame | |
| h2o.HGLMMetrics | Retrieve HGLM ModelMetrics | |
| .h2o.__IMPORT | Import/Export Endpoints | |
| h2o.exportHDFS | Export a Model to HDFS | |
| h2o-package | H2O R Interface | |
| h2o.aggregated_frame | Retrieve an aggregated frame from an Aggregator model | |
| H2OCoxPHModelSummary-class | The H2OCoxPHModelSummary object. | |
| H2OAutoML-class | The H2OAutoML class | |
| H2OConnection-class | The H2OConnection class. | |
| H2OConnectionMutableState | The H2OConnectionMutableState class | |
| h2o.assign | Rename an H2O object. | |
| h2o.aggregator | Build an Aggregated Frame | |
| h2o.clearLog | Delete All H2O R Logs | |
| h2o.as_date | Convert between character representations and objects of Date class | |
| H2OTree-class | The H2OTree class. | |
| Keyed-class | Virtual Keyed class | |
| aaa | Starting H2O For examples | |
| && | Logical and for H2OFrames | |
| h2o.auc | Retrieve the AUC | |
| h2o.keyof | Method on Keyed objects allowing to obtain their key. | |
| 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.clusterInfo | Print H2O cluster info | |
| h2o.coxph | Trains a Cox Proportional Hazards Model (CoxPH) on an H2O dataset | |
| h2o.getVersion | Get h2o version | |
| h2o.decryptionSetup | Setup a Decryption Tool | |
| h2o.import_mojo | Imports a MOJO under given path, creating a Generic model with it. | |
| h2o.gainsLift | Access H2O Gains/Lift Tables | |
| h2o.cosh | Compute the hyperbolic cosine of x | |
| Logical-or | Logical or for H2OFrames | |
| h2o.distance | Compute a pairwise distance measure between all rows of two numeric H2OFrames. | |
| h2o.dimnames | Column names of an H2OFrame | |
| .pkg.env | The H2O Package Environment | |
| .h2o.__DKV | Removal Endpoints | |
| h2o.get_automl | Get an R object that is a subclass of H2OAutoML | |
| h2o.isolationForest | Trains an Isolation Forest model | |
| h2o.fillna | fillNA | |
| h2o.hist | Compute A Histogram | |
| h2o.ls | List Keys on an H2O Cluster | |
| h2o.gbm | Build gradient boosted classification or regression trees | |
| h2o.anyFactor | Check H2OFrame columns for factors | |
| h2o.downloadAllLogs | Download H2O Log Files to Disk | |
| feature_frequencies.H2OModel | Retrieve the number of occurrences of each feature for given observations Available for GBM, Random Forest and Isolation Forest models. | |
| .h2o.__EXPORT_FILES | Export Files Endpoint Generator | |
| h2o.hit_ratio_table | Retrieve the Hit Ratios | |
| h2o.lstrip | Strip set from left | |
| h2o.cluster_sizes | Retrieve the cluster sizes | |
| .h2o.__FRAMES | Inspect/Summary Endpoints | |
| h2o.columns_by_type | Obtain a list of columns that are specified by `coltype` | |
| h2o.aic | Retrieve the Akaike information criterion (AIC) value | |
| australia | Australia Coastal Data | |
| as.vector.H2OFrame | Convert an H2OFrame to a vector | |
| .h2o.is_progress | Check if Progress Bar is Enabled | |
| .h2o.__checkConnectionHealth | Check H2O Server Health | |
| h2o.download_model | Download the model in binary format. | |
| h2o.min | Returns the minima of the input values. | |
| .h2o.primitives | Map of operations known to H2O | |
| h2o.clusterIsUp | Determine if an H2O cluster is up or not | |
| h2o.arrange | Sorts an H2O frame by columns | |
| .skip_if_not_developer | H2O <-> R Communication and Utility Methods | |
| h2o.show_progress | Enable Progress Bar | |
| .h2o.doGET | Just like doRawGET but fills in the default h2oRestApiVersion if none is provided | |
| h2o.biases | Return the respective bias vector | |
| H2OModelFuture-class | H2O Future Model | |
| h2o.centers | Retrieve the Model Centers | |
| h2o.floor | Take a single numeric argument and return a numeric vector with the largest integers | |
| h2o.betweenss | Get the between cluster sum of squares | |
| H2OClusteringModel-class | The H2OClusteringModel object. | |
| h2o.ceiling | Take a single numeric argument and return a numeric vector with the smallest integers | |
| .h2o.__LOGANDECHO | Log and Echo Endpoint | |
| h2o.import_sql_select | Import SQL table that is result of SELECT SQL query into H2O | |
| h2o.download_mojo | Download the model in MOJO format. | |
| h2o.listTimezones | List all of the Time Zones Acceptable by the H2O cluster. | |
| h2o.mean_residual_deviance | Retrieve the Mean Residual Deviance value | |
| h2o.levels | Return the levels from the column requested column. | |
| h2o.null_deviance | Retrieve the null deviance | |
| h2o.randomForest | Build a Random Forest model | |
| h2o.predict_json | H2O Prediction from R without having H2O running | |
| h2o.xgboost | Build an eXtreme Gradient Boosting model | |
| h2o.mean_per_class_error | Retrieve the mean per class error | |
| h2o.ascharacter | Convert H2O Data to Characters | |
| apply | Apply on H2O Datasets | |
| h2o.dayOfWeek | Convert Milliseconds to Day of Week in H2O Datasets | |
| h2o.day | Convert Milliseconds to Day of Month in H2O Datasets | |
| h2o.cross_validation_holdout_predictions | Retrieve the cross-validation holdout predictions | |
| h2o.computeGram | Compute weighted gram matrix. | |
| h2o.cross_validation_models | Retrieve the cross-validation models | |
| h2o.downloadCSV | Download H2O Data to Disk | |
| h2o.findSynonyms | Find synonyms using a word2vec model. | |
| .h2o.doPOST | Just like doRawPOST but fills in the default h2oRestApiVersion if none is provided | |
| ModelAccessors | Accessor Methods for H2OModel Object | |
| .h2o.__MODELS | Model Endpoint | |
| H2OModelMetrics-class | The H2OModelMetrics Object. | |
| h2o.mktime | Compute msec since the Unix Epoch | |
| h2o.clusterStatus | Return the status of the cluster | |
| h2o.flow | Open H2O Flow | |
| h2o.connect | Connect to a running H2O instance. | |
| h2o.confusionMatrix | Access H2O Confusion Matrices | |
| h2o.isfactor | Check if factor | |
| as.numeric | Convert H2O Data to Numeric | |
| h2o.shutdown | Shut Down H2O Instance | |
| h2o.null_dof | Retrieve the null degrees of freedom | |
| h2o.rep_len | Replicate Elements of Vectors or Lists into H2O | |
| h2o.print | Print An H2OFrame | |
| h2o.group_by | Group and Apply by Column | |
| as.character.H2OFrame | Convert an H2OFrame to a String | |
| h2o.sd | Standard Deviation of a column of data. | |
| h2o.cross_validation_fold_assignment | Retrieve the cross-validation fold assignment | |
| h2o.createFrame | Data H2OFrame Creation in H2O | |
| h2o.r2 | Retrieve the R2 value | |
| h2o.deepwater | Build a Deep Learning model using multiple native GPU backends | |
| 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.deeplearning | Build a Deep Neural Network model using CPUs | |
| h2o.getFrame | Get an R Reference to an H2O Dataset, that will NOT be GC'd by default | |
| h2o.getModel | Get an R reference to an H2O model | |
| h2o.filterNACols | Filter NA Columns | |
| h2o.kmeans | Performs k-means clustering on an H2O dataset | |
| h2o.download_pojo | Download the Scoring POJO (Plain Old Java Object) of an H2O Model | |
| h2o.removeVecs | Delete Columns from an H2OFrame | |
| h2o.str | Display the structure of an H2OFrame object | |
| h2o.signif | Round doubles/floats to the given number of significant digits. | |
| h2o.sdev | Retrieve the standard deviations of principal components | |
| h2o.entropy | Shannon entropy | |
| h2o.target_encode_transform | Deprecated API. Please use h2o.targetencoder model instead. Transform Frame by Target Encoding Map | |
| h2o.stringdist | Compute element-wise string distances between two H2OFrames | |
| h2o.unique | H2O Unique | |
| h2o.target_encode_fit | Deprecated API. Please use h2o.targetencoder model instead. | |
| is.character | Check if character | |
| .h2o.__RAPIDS | Rapids Endpoint | |
| generate_col_ind | CHeck to see if the column names/indices entered is valid for the dataframe given. This is an internal function | |
| .addParm | TODO: No objects in this file are being used. Either remove file or use objects. | |
| h2o.get_leaderboard | Retrieve the leaderboard from the AutoML instance. | |
| h2o.hour | Convert Milliseconds to Hour of Day in H2O Datasets | |
| h2o.giniCoef | Retrieve the GINI Coefficcient | |
| h2o.grid | H2O Grid Support | |
| h2o.no_progress | Disable Progress Bar | |
| h2o.performance | Model Performance Metrics in H2O | |
| h2o.get_ntrees_actual | Retrieve actual number of trees for tree algorithms | |
| h2o.bottomN | H2O bottomN | |
| .h2o.__PARSE_SETUP | Parse Endpoints | |
| h2o.asnumeric | Convert H2O Data to Numerics | |
| colnames | Returns the column names of an H2OFrame | |
| .h2o.doRawGET | Perform a low-level HTTP GET operation on an H2O instance | |
| h2o.transform,H2OTargetEncoderModel-method | Applies target encoding to a given dataset | |
| h2o.list_core_extensions | List registered core extensions | |
| is.factor | Check if factor | |
| print.H2OTable | Print method for H2OTable objects | |
| h2o.upload_mojo | Imports a MOJO from a local filesystem, creating a Generic model with it. | |
| h2o.transform,H2OWordEmbeddingModel-method | Transform words (or sequences of words) to vectors using a word2vec model. | |
| print.H2OFrame | Print An H2OFrame | |
| h2o.word2vec | Trains a word2vec model on a String column of an H2O data frame | |
| h2o.cummin | Return the cumulative min over a column or across a row | |
| h2o.glm | Fit a generalized linear model | |
| h2o.merge | Merge Two H2O Data Frames | |
| h2o.is_client | Check Client Mode Connection | |
| h2o.mse | Retrieves Mean Squared Error Value | |
| h2o.cross_validation_predictions | Retrieve the cross-validation predictions | |
| h2o.init | Initialize and Connect to H2O | |
| h2o.insertMissingValues | Insert Missing Values into an H2OFrame | |
| h2o.month | Convert Milliseconds to Months in H2O Datasets | |
| h2o.interaction | Categorical Interaction Feature Creation in H2O | |
| .collapse | Helper Collapse Function | |
| h2o.log | Compute the logarithm of x | |
| h2o.pivot | Pivot a frame | |
| h2o.naiveBayes | Compute naive Bayes probabilities on an H2O dataset. | |
| h2o.logAndEcho | Log a message on the server-side logs | |
| h2o.logloss | Retrieve the Log Loss Value | |
| h2o.median | H2O Median | |
| h2o.ifelse | H2O Apply Conditional Statement | |
| h2o.trunc | Truncate values in x toward 0 | |
| h2o.isnumeric | Check if numeric | |
| h2o.list_jobs | Return list of jobs performed by the H2O cluster | |
| h2o.melt | Converts a frame to key-value representation while optionally skipping NA values. Inverse operation to h2o.pivot. | |
| get_seed.H2OModel | Get the seed from H2OModel which was used during training. If a user does not set the seed parameter before training, the seed is autogenerated. It returns seed as the string if the value is bigger than the integer. For example, an autogenerated seed is always long so that the seed in R is a string. | |
| h2o.kurtosis | Kurtosis of a column | |
| .h2o.__REST_API_VERSION | H2O Package Constants | |
| .h2o.__W2V_SYNONYMS | Word2Vec Endpoints | |
| .verify_dataxy | Used to verify data, x, y and turn into the appropriate things | |
| h2o.names | Column names of an H2OFrame | |
| h2o.aucpr | Retrieve the AUCPR (Area Under Precision Recall Curve) | |
| h2o.nrow | Return the number of rows present in x. | |
| h2o.scoreHistory | Retrieve Model Score History | |
| h2o.rm | Delete Objects In H2O | |
| h2o.rmse | Retrieves Root Mean Squared Error Value | |
| h2o.set_s3_credentials | Creates a new Amazon S3 client internally with specified credentials. | |
| h2o.reconstruct | Reconstruct Training Data via H2O GLRM Model | |
| h2o.scale | Scaling and Centering of an H2OFrame | |
| h2o.rbind | Combine H2O Datasets by Rows | |
| h2o.substring | Substring | |
| h2o.prod | Return the product of all the values present in its arguments. | |
| h2o.round | Round doubles/floats to the given number of decimal places. | |
| h2o.log10 | Compute the log10 of x | |
| h2o.metric | H2O Model Metric Accessor Functions | |
| h2o.nchar | String length | |
| h2o.skewness | Skewness of a column | |
| h2o.target_encode_apply | Apply Target Encoding Map to Frame | |
| plot.H2OTabulate | Plot an H2O Tabulate Heatmap | |
| h2o.week | Convert Milliseconds to Week of Week Year in H2O Datasets | |
| scale | Scaling and Centering of an H2OFrame | |
| h2o.toupper | Convert strings to uppercase | |
| h2o.trim | Trim Space | |
| h2o.totss | Get the total sum of squares. | |
| h2o.target_encode_create | Create Target Encoding Map | |
| h2o.weights | Retrieve the respective weight matrix | |
| h2o.sum | Compute the frame's sum by-column (or by-row). | |
| plot.H2OModel | Plot an H2O Model | |
| h2o.asfactor | Convert H2O Data to Factors | |
| h2o.getGLMFullRegularizationPath | Extract full regularization path from a GLM model | |
| h2o.getFutureModel | Get future model | |
| h2o.cor | Correlation of columns. | |
| h2o.abs | Compute the absolute value of x | |
| h2o.centersSTD | Retrieve the Model Centers STD | |
| h2o.acos | Compute the arc cosine of x | |
| h2o.automl | Automatic Machine Learning | |
| h2o.cut | Cut H2O Numeric Data to Factor | |
| str.H2OFrame | Display the structure of an H2OFrame object | |
| h2o.all | Given a set of logical vectors, are all of the values true? | |
| h2o.gsub | String Global Substitute | |
| h2o.cummax | Return the cumulative max over a column or across a row | |
| h2o.cos | Compute the cosine of x | |
| h2o.deepwater.available | Determines whether Deep Water is available | |
| h2o.saveGrid | Saves an existing Grid of models into a given folder. | |
| h2o.openLog | View H2O R Logs | |
| h2o.describe | H2O Description of A Dataset | |
| h2o.cumsum | Return the cumulative sum over a column or across a row | |
| h2o.exp | Compute the exponential function of x | |
| h2o.centroid_stats | Retrieve centroid statistics | |
| h2o.impute | Basic Imputation of H2O Vectors | |
| h2o.ddply | Split H2O Dataset, Apply Function, and Return Results | |
| h2o.exportFile | Export an H2O Data Frame (H2OFrame) to a File or to a collection of Files. | |
| h2o.getGrid | Get a grid object from H2O distributed K/V store. | |
| staged_predict_proba.H2OModel | Predict class probabilities at each stage of an H2O Model | |
| h2o.cbind | Combine H2O Datasets by Columns | |
| h2o.quantile | Quantiles of H2O Frames. | |
| h2o.find_row_by_threshold | Find the threshold, give the max metric. No duplicate thresholds allowed | |
| h2o.coef | Return the coefficients that can be applied to the non-standardized data. | |
| h2o.dct | Compute DCT of an H2OFrame | |
| h2o.mean | Compute the frame's mean by-column (or by-row). | |
| h2o.partialPlot | Partial Dependence Plots | |
| h2o.parseSetup | Get a parse setup back for the staged data. | |
| h2o.ncol | Return the number of columns present in x. | |
| h2o.rmsle | Retrieve the Root Mean Squared Log Error | |
| h2o.proj_archetypes | Convert Archetypes to Features from H2O GLRM Model | |
| h2o.kfold_column | Produce a k-fold column vector. | |
| h2o.difflag1 | Conduct a lag 1 transform on a numeric H2OFrame column | |
| h2o.cumprod | Return the cumulative product over a column or across a row | |
| h2o.na_omit | Remove Rows With NAs | |
| h2o.head | Return the Head or Tail of an H2O Dataset. | |
| h2o.log1p | Compute the log1p of x | |
| h2o.import_sql_table | Import SQL Table into H2O | |
| h2o.loadModel | Load H2O Model from HDFS or Local Disk | |
| h2o.getId | Get back-end distributed key/value store id from an H2OFrame. | |
| h2o.killMinus3 | Dump the stack into the JVM's stdout. | |
| h2o.strsplit | String Split | |
| summary,H2OCoxPHModel-method | Summary method for H2OCoxPHModel objects | |
| h2o.which | Which indices are TRUE? | |
| h2o.transform | Use H2O Transformation model and apply the underlying transformation | |
| h2o.tan | Compute the tangent of x | |
| h2o.sin | Compute the sine of x | |
| h2o.saveModel | Save an H2O Model Object to Disk | |
| h2o.dim | Returns the number of rows and columns for an H2OFrame object. | |
| housevotes | United States Congressional Voting Records 1984 | |
| h2o.loadGrid | Loads previously saved grid with all it's models from the same folder | |
| zzz | Shutdown H2O cluster after examples run | |
| h2o.sub | String Substitute | |
| iris | Edgar Anderson's Iris Data | |
| h2o.tanh | Compute the hyperbolic tangent of x | |
| h2o.networkTest | View Network Traffic Speed | |
| h2o.max | Returns the maxima of the input values. | |
| predict.H2OAutoML | Predict on an AutoML object | |
| h2o.transform_word2vec | Transform words (or sequences of words) to vectors using a word2vec model. | |
| h2o.toFrame | Convert a word2vec model into an H2OFrame | |
| h2o.targetencoder | Transformation of a categorical variable with a mean value of the target variable | |
| h2o.nacnt | Count of NAs per column | |
| h2o.which_max | Which indice contains the max value? | |
| predict.H2OModel | Predict on an H2O Model | |
| h2o.log2 | Compute the log2 of x | |
| h2o.nlevels | Get the number of factor levels for this frame. | |
| h2o.rstrip | Strip set from right | |
| h2o.varsplits | Retrieve per-variable split information for a given Isolation Forest model. Output will include: - count - The number of times a variable was used to make a split. - aggregated_split_ratios - The split ratio is defined as "abs(#left_observations - #right_observations) / #before_split". Even splits (#left_observations approx the same as #right_observations) contribute less to the total aggregated split ratio value for the given feature; highly imbalanced splits (eg. #left_observations >> #right_observations) contribute more. - aggregated_split_depths - The sum of all depths of a variable used to make a split. (If a variable is used on level N of a tree, then it contributes with N to the total aggregate.) | |
| 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.startLogging | Start Writing H2O R Logs | |
| h2o.makeGLMModel | Set betas of an existing H2O GLM Model | |
| h2o.parseRaw | H2O Data Parsing | |
| h2o.removeAll | Remove All Objects on the H2O Cluster | |
| h2o.range | Returns a vector containing the minimum and maximum of all the given arguments. | |
| is.numeric | Check if numeric | |
| h2o.tolower | Convert strings to lowercase | |
| h2o.relevel | Reorders levels of an H2O factor, similarly to standard R's relevel. | |
| h2o.getTimezone | Get the Time Zone on the H2O cluster Returns a string | |
| h2o.list_all_extensions | List all H2O registered extensions | |
| h2o.importFile | Import Files into H2O | |
| h2o.find_threshold_by_max_metric | Find the threshold, give the max metric | |
| h2o.generic | Imports a generic model into H2O. Such model can be used then used for scoring and obtaining additional information about the model. The imported model has to be supported by H2O. | |
| h2o.ischaracter | Check if character | |
| h2o.glrm | Generalized low rank decomposition of an H2O data frame | |
| h2o.genericModel | Imports a model under given path, creating a Generic model with it. | |
| h2o.getTypes | Get the types-per-column | |
| h2o.grep | Search for matches to an argument pattern | |
| h2o.isax | iSAX | |
| h2o.psvm | Trains a Support Vector Machine model on an H2O dataset | |
| h2o.splitFrame | Split an H2O Data Set | |
| h2o.import_hive_table | Import Hive Table into H2O | |
| h2o.predict | Predict on an H2O Model | |
| h2o.match | Value Matching in H2O | |
| h2o.mae | Retrieve the Mean Absolute Error Value | |
| h2o.make_metrics | Create Model Metrics from predicted and actual values in H2O | |
| h2o.list_api_extensions | List registered API extensions | |
| h2o.setLevels | Set Levels of H2O Factor Column | |
| h2o.runif | Produce a Vector of Random Uniform Numbers | |
| h2o.stackedEnsemble | Builds a Stacked Ensemble | |
| is.h2o | Is H2O Frame object | |
| h2o.svd | Singular value decomposition of an H2O data frame using the power method | |
| h2o.summary | Summarizes the columns of an H2OFrame. | |
| h2o.tokenize | Tokenize String | |
| h2o.varimp_plot | Plot Variable Importances | |
| h2o.setTimezone | Set the Time Zone on the H2O cluster | |
| h2o.xgboost.available | Determines whether an XGBoost model can be built | |
| h2o.num_iterations | Retrieve the number of iterations. | |
| h2o.mojo_predict_csv | H2O Prediction from R without having H2O running | |
| h2o.mojo_predict_df | H2O Prediction from R without having H2O running | |
| h2o.prcomp | Principal component analysis of an H2O data frame | |
| h2o.saveModelDetails | Save an H2O Model Details | |
| h2o.num_valid_substrings | Count of substrings >= 2 chars that are contained in file | |
| h2o.residual_dof | Retrieve the residual degrees of freedom | |
| h2o.std_coef_plot | Plot Standardized Coefficient Magnitudes | |
| h2o.residual_deviance | Retrieve the residual deviance | |
| h2o.sqrt | Compute the square root of x | |
| h2o.year | Convert Milliseconds to Years in H2O Datasets | |
| summary,H2OGrid-method | Format grid object in user-friendly way | |
| summary,H2OModel-method | Print the Model Summary | |
| h2o.varimp | Retrieve the variable importance. | |
| prostate | Prostate Cancer Study | |
| h2o.saveMojo | Save an H2O Model Object as Mojo to Disk | |
| h2o.which_min | Which index contains the min value? | |
| predict_leaf_node_assignment.H2OModel | Predict the Leaf Node Assignment on an H2O Model | |
| predict_contributions.H2OModel | Predict feature contributions - SHAP values on an H2O Model (only GBM and XGBoost models). | |
| length,H2OTree-method | Overrides the behavior of length() function on H2OTree class. Returns number of nodes in an H2OTree | |
| h2o.table | Cross Tabulation and Table Creation in H2O | |
| h2o.stopLogging | Stop Writing H2O R Logs | |
| names.H2OFrame | Column names of an H2OFrame | |
| h2o.tabulate | Tabulation between Two Columns of an H2OFrame | |
| h2o.var | Variance of a column or covariance of columns. | |
| h2o.tot_withinss | Get the total within cluster sum of squares. | |
| h2o.topN | H2O topN | |
| h2o.withinss | Get the Within SS | |
| use.package | Use optional package | |
| range.H2OFrame | Range of an H2O Column | |
| walking | Muscular Actuations for Walking Subject | |
| No Results! | ||
Last month downloads
Details
| Type | Package |
| Date | 2020-01-20 |
| License | Apache License (== 2.0) |
| URL | https://github.com/h2oai/h2o-3 |
| BugReports | https://0xdata.atlassian.net/projects/PUBDEV |
| NeedsCompilation | no |
| SystemRequirements | Java (>= 8) |
| 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' 'targetencoder_deprecated.R' 'targetencoder.R' 'import.R' 'isolationforest.R' 'parse.R' 'export.R' 'edicts.R' 'models.R' 'coxph.R' 'coxphutils.R' 'kmeans.R' 'gbm.R' 'generic.R' 'glm.R' 'glrm.R' 'pca.R' 'svd.R' 'psvm.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' |
| RoxygenNote | 7.0.2 |
| Packaged | 2020-01-20 19:04:08 UTC; jenkins |
| Repository | CRAN |
| Date/Publication | 2020-01-22 11:20:10 UTC |
| suggests | bit64 (>= 0.9.7) , data.table (>= 1.9.8) , ggplot2 , Matrix , mlbench , plot3Drgl (>= 1.0.1) , rgl (>= 0.100.19) , 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 |
Include our badge in your README
[](http://www.rdocumentation.org/packages/h2o)