h2o v3.30.1.2
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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 (GLM), Gradient Boosting Machines (including XGBoost), Random Forests,
Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes,
Generalized Additive Models (GAM), Cox Proportional Hazards, K-Means, PCA,
Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Functions in h2o
| Name | Description | |
| H2OAutoML-class | The H2OAutoML class | |
| H2OConnection-class | The H2OConnection class. | |
| H2OCoxPHModel-class | The H2OCoxPHModel object. | |
| H2OClusteringModel-class | The H2OClusteringModel object. | |
| H2OFrame-class | The H2OFrame class | |
| H2OFrame-Extract | Extract or Replace Parts of an H2OFrame Object | |
| H2OConnectionMutableState | The H2OConnectionMutableState class | |
| Ops.H2OFrame | S3 Group Generic Functions for H2O | |
| H2OGrid-class | H2O Grid | |
| H2OCoxPHModelSummary-class | The H2OCoxPHModelSummary object. | |
| apply | Apply on H2O Datasets | |
| as.vector.H2OFrame | Convert an H2OFrame to a vector | |
| H2OSplitNode-class | The H2OSplitNode class. | |
| H2OSegmentModelsFuture-class | H2O Future Segment Models | |
| H2OLeafNode-class | The H2OLeafNode class. | |
| .h2o.__DKV | Removal Endpoints | |
| H2OSegmentModels-class | H2O Segment Models | |
| H2ONode-class | The H2ONode class. | |
| australia | Australia Coastal Data | |
| H2OModel-class | The H2OModel object. | |
| H2OTree-class | The H2OTree class. | |
| .h2o.doPOST | Just like doRawPOST but fills in the default h2oRestApiVersion if none is provided | |
| .h2o.__EXPORT_FILES | Export Files Endpoint Generator | |
| .h2o.doRawGET | Perform a low-level HTTP GET operation on an H2O instance | |
| .h2o.doRawPOST | Perform a low-level HTTP POST operation on an H2O instance | |
| .h2o.doSafeGET | Perform a safe (i.e. error-checked) HTTP GET request to an H2O cluster. | |
| H2OModelFuture-class | H2O Future Model | |
| as.data.frame.H2OFrame | Converts parsed H2O data into an R data frame | |
| Keyed-class | Virtual Keyed class | |
| 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. | |
| ModelAccessors | Accessor Methods for H2OModel Object | |
| .addParm | TODO: No objects in this file are being used. Either remove file or use objects. | |
| as.character.H2OFrame | Convert an H2OFrame to a String | |
| Logical-or | Logical or for H2OFrames | |
| dimnames.H2OFrame | Column names of an H2OFrame | |
| h2o-package | H2O R Interface | |
| as.matrix.H2OFrame | Convert an H2OFrame to a matrix | |
| h2o.centroid_stats | Retrieve centroid statistics | |
| h2o.clearLog | Delete All H2O R Logs | |
| .h2o.__CREATE_FRAME | H2OFrame Manipulation | |
| as.numeric | Convert H2O Data to Numeric | |
| .h2o.__MODEL_METRICS | Model Metrics Endpoint | |
| .h2o.perfect_auc | Internal function that calculates a precise AUC from given probabilities and actual responses. | |
| .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.aggregator | Build an Aggregated Frame | |
| as.data.frame.H2OSegmentModels | Converts a collection of Segment Models to a data.frame | |
| .h2o.__DECRYPTION_SETUP | Decryption Endpoints | |
| .h2o.__PARSE_SETUP | Parse Endpoints | |
| colnames | Returns the column names of an H2OFrame | |
| h2o.aic | Retrieve the Akaike information criterion (AIC) value | |
| h2o.assign | Rename an H2O object. | |
| h2o.asnumeric | Convert H2O Data to Numerics | |
| h2o.clusterIsUp | Determine if an H2O cluster is up or not | |
| h2o.betweenss | Get the between cluster sum of squares | |
| h2o.clusterInfo | Print H2O cluster info | |
| h2o.automl | Automatic Machine Learning | |
| H2OModelMetrics-class | The H2OModelMetrics Object. | |
| && | Logical and for H2OFrames | |
| aaa | Starting H2O For examples | |
| .h2o.__MODELS | Model Endpoint | |
| dim.H2OFrame | Returns the Dimensions of an H2OFrame | |
| .h2o.__RAPIDS | Rapids Endpoint | |
| h2o.cross_validation_models | Retrieve the cross-validation models | |
| h2o.cross_validation_predictions | Retrieve the cross-validation predictions | |
| h2o.dim | Returns the number of rows and columns for an H2OFrame object. | |
| h2o.confusionMatrix | Access H2O Confusion Matrices | |
| h2o.downloadAllLogs | Download H2O Log Files to Disk | |
| h2o.computeGram | Compute weighted gram matrix. | |
| h2o.distance | Compute a pairwise distance measure between all rows of two numeric H2OFrames. | |
| h2o.exportHDFS | Export a Model to HDFS | |
| h2o.fillna | fillNA | |
| .h2o.__REST_API_VERSION | H2O Package Constants | |
| h2o.HGLMMetrics | Retrieve HGLM ModelMetrics | |
| .h2o.__checkConnectionHealth | Check H2O Server Health | |
| .h2o.__MODEL_BUILDERS | Model Builder Endpoint Generator | |
| as.factor | Convert H2O Data to Factors | |
| h2o.ascharacter | Convert H2O Data to Characters | |
| h2o.centers | Retrieve the Model Centers | |
| h2o.asfactor | Convert H2O Data to Factors | |
| h2o.abs | Compute the absolute value of x | |
| h2o.centersSTD | Retrieve the Model Centers STD | |
| .h2o.doGET | Just like doRawGET but fills in the default h2oRestApiVersion if none is provided | |
| .collapse | Helper Collapse Function | |
| .h2o.__JOBS | Administrative Endpoints | |
| as.h2o | Create H2OFrame | |
| .h2o.primitives | Map of operations known to H2O | |
| h2o.filterNACols | Filter NA Columns | |
| h2o.findSynonyms | Find synonyms using a word2vec model. | |
| h2o.getConnection | Retrieve an H2O Connection | |
| h2o.genericModel | Imports a model under given path, creating a Generic model with it. | |
| h2o.entropy | Shannon entropy | |
| h2o.drop_duplicates | Drops duplicated rows. | |
| h2o.dimnames | Column names of an H2OFrame | |
| .h2o.doSafePOST | Perform a safe (i.e. error-checked) HTTP POST request to an H2O cluster. | |
| .h2o.is_progress | Check if Progress Bar is Enabled | |
| .h2o.__LOGANDECHO | Log and Echo Endpoint | |
| h2o.gbm | Build gradient boosted classification or regression trees | |
| .h2o.__ALL_CAPABILITIES | Capabilities endpoints | |
| feature_frequencies.H2OModel | Retrieve the number of occurrences of each feature for given observations Available for GBM, Random Forest and Isolation Forest models. | |
| h2o.is_client | Check Client Mode Connection | |
| generate_col_ind | CHeck to see if the column names/indices entered is valid for the dataframe given. This is an internal function | |
| .h2o.__W2V_SYNONYMS | Word2Vec Endpoints | |
| .h2o.__SEGMENT_MODELS_BUILDERS | Segment Models Builder Endpoint Generator | |
| .skip_if_not_developer | H2O <-> R Communication and Utility Methods | |
| h2o.isax | iSAX | |
| .h2o.__IMPORT | Import/Export Endpoints | |
| .h2o.__FRAMES | Inspect/Summary Endpoints | |
| .pkg.env | The H2O Package Environment | |
| 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.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.createFrame | Data H2OFrame Creation in H2O | |
| h2o.coxph | Trains a Cox Proportional Hazards Model (CoxPH) on an H2O dataset | |
| h2o.all | Given a set of logical vectors, are all of the values true? | |
| h2o.keyof | Method on Keyed objects allowing to obtain their key. | |
| h2o.kfold_column | Produce a k-fold column vector. | |
| h2o.acos | Compute the arc cosine of x | |
| h2o.aggregated_frame | Retrieve an aggregated frame from an Aggregator model | |
| .verify_dataxy | Used to verify data, x, y and turn into the appropriate things | |
| 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.getTimezone | Get the Time Zone on the H2O cluster Returns a string | |
| h2o.biases | Return the respective bias vector | |
| h2o.bottomN | H2O bottomN | |
| h2o.anyFactor | Check H2OFrame columns for factors | |
| h2o.loadGrid | Loads previously saved grid with all it's models from the same folder | |
| h2o.day | Convert Milliseconds to Day of Month in H2O Datasets | |
| h2o.decryptionSetup | Setup a Decryption Tool | |
| h2o.ddply | Split H2O Dataset, Apply Function, and Return Results | |
| h2o.cut | Cut H2O Numeric Data to Factor | |
| h2o.floor | Take a single numeric argument and return a numeric vector with the largest integers | |
| h2o.loadModel | Load H2O Model from HDFS or Local Disk | |
| h2o.connect | Connect to a running H2O instance. | |
| h2o.cummax | Return the cumulative max over a column or across a row | |
| h2o.cor | Correlation of columns. | |
| h2o.cummin | Return the cumulative min over a column or across a row | |
| h2o.max | Returns the maxima of the input values. | |
| h2o.getTypes | Get the types-per-column | |
| h2o.getVersion | Get h2o version | |
| h2o.get_automl | Get an R object that is a subclass of H2OAutoML | |
| h2o.arrange | Sorts an H2O frame by columns | |
| h2o.import_hive_table | Import Hive Table into H2O | |
| h2o.auc | Retrieve the AUC | |
| h2o.aucpr | Retrieve the AUCPR (Area Under Precision Recall Curve) | |
| h2o.as_date | Convert between character representations and objects of Date class | |
| h2o.deepfeatures | Feature Generation via H2O Deep Learning | |
| h2o.cbind | Combine H2O Datasets by Columns | |
| h2o.import_mojo | Imports a MOJO under given path, creating a Generic model with it. | |
| h2o.exportFile | Export an H2O Data Frame (H2OFrame) to a File or to a collection of Files. | |
| h2o.deeplearning | Build a Deep Neural Network model using CPUs | |
| h2o.exp | Compute the exponential function of x | |
| h2o.find_threshold_by_max_metric | Find the threshold, give the max metric | |
| h2o.find_row_by_threshold | Find the threshold, give the max metric. No duplicate thresholds allowed | |
| h2o.ceiling | Take a single numeric argument and return a numeric vector with the smallest integers | |
| h2o.flow | Open H2O Flow | |
| h2o.ischaracter | Check if character | |
| h2o.mean | Compute the frame's mean by-column (or by-row). | |
| h2o.getGrid | Get a grid object from H2O distributed K/V store. | |
| h2o.clusterStatus | Return the status of the cluster | |
| h2o.get_segment_models | Retrieves an instance of H2OSegmentModels for a given id. | |
| h2o.ifelse | H2O Apply Conditional Statement | |
| h2o.giniCoef | Retrieve the GINI Coefficcient | |
| h2o.getId | Get back-end distributed key/value store id from an H2OFrame. | |
| h2o.importFile | Import Files into H2O | |
| h2o.mean_per_class_error | Retrieve the mean per class error | |
| h2o.cluster_sizes | Retrieve the cluster sizes | |
| h2o.cross_validation_fold_assignment | Retrieve the cross-validation fold assignment | |
| h2o.colnames | Return column names of an H2OFrame | |
| h2o.log10 | Compute the log10 of x | |
| h2o.isfactor | Check if factor | |
| h2o.logAndEcho | Log a message on the server-side logs | |
| h2o.min | Returns the minima of the input values. | |
| h2o.logloss | Retrieve the Log Loss Value | |
| h2o.log | Compute the logarithm of x | |
| h2o.mktime | Compute msec since the Unix Epoch | |
| h2o.null_deviance | Retrieve the null deviance | |
| h2o.get_leaderboard | Retrieve the leaderboard from the AutoML instance. | |
| h2o.cross_validation_holdout_predictions | Retrieve the cross-validation holdout predictions | |
| h2o.null_dof | Retrieve the null degrees of freedom | |
| h2o.get_ntrees_actual | Retrieve actual number of trees for tree algorithms | |
| h2o.mean_residual_deviance | Retrieve the Mean Residual Deviance value | |
| h2o.names | Column names of an H2OFrame | |
| h2o.prcomp | Principal component analysis of an H2O data frame | |
| h2o.parseSetup | Get a parse setup back for the staged data. | |
| h2o.naiveBayes | Compute naive Bayes probabilities on an H2O dataset. | |
| h2o.partialPlot | Partial Dependence Plots | |
| h2o.removeAll | Remove All Objects on the H2O Cluster | |
| h2o.predict | Predict on an H2O Model | |
| h2o.removeVecs | Delete Columns from an H2OFrame | |
| h2o.columns_by_type | Obtain a list of columns that are specified by `coltype` | |
| h2o.group_by | Group and Apply by Column | |
| h2o.upload_model | Upload a binary model from the provided local path to the H2O cluster. (H2O model can be saved in a binary form either by saveModel() or by download_model() function.) | |
| h2o.varimp | Retrieve the variable importance. | |
| h2o.strsplit | String Split | |
| h2o.tanh | Compute the hyperbolic tangent of x | |
| h2o.stringdist | Compute element-wise string distances between two H2OFrames | |
| h2o.var | Variance of a column or covariance of columns. | |
| h2o.upload_mojo | Imports a MOJO from a local filesystem, creating a Generic model with it. | |
| is.character | Check if character | |
| h2o.target_encode_apply | Apply Target Encoding Map to Frame | |
| h2o.cumprod | Return the cumulative product over a column or across a row | |
| h2o.predict_json | H2O Prediction from R without having H2O running | |
| h2o.gsub | String Global Substitute | |
| predict_contributions.H2OModel | Predict feature contributions - SHAP values on an H2O Model (only DRF, GBM and XGBoost models). | |
| predict_leaf_node_assignment.H2OModel | Predict the Leaf Node Assignment on an H2O Model | |
| is.factor | Check if factor | |
| show,H2OAutoML-method | Format AutoML object in user-friendly way | |
| scale | Scaling and Centering of an H2OFrame | |
| h2o.reset_threshold | Reset model threshold and return old threshold value. | |
| h2o.print | Print An H2OFrame | |
| h2o.rep_len | Replicate Elements of Vectors or Lists into H2O | |
| h2o.saveGrid | Saves an existing Grid of models into a given folder. | |
| h2o.cos | Compute the cosine of x | |
| h2o.saveModel | Save an H2O Model Object to Disk | |
| h2o.describe | H2O Description of A Dataset | |
| h2o.difflag1 | Conduct a lag 1 transform on a numeric H2OFrame column | |
| h2o.cumsum | Return the cumulative sum over a column or across a row | |
| h2o.insertMissingValues | Insert Missing Values into an H2OFrame | |
| h2o.download_mojo | Download the model in MOJO format. | |
| h2o.grep | Search for matches to an argument pattern | |
| h2o.getFrame | Get an R Reference to an H2O Dataset, that will NOT be GC'd by default | |
| h2o.getGLMFullRegularizationPath | Extract full regularization path from a GLM model | |
| h2o.download_pojo | Download the Scoring POJO (Plain Old Java Object) of an H2O Model | |
| h2o.grid | H2O Grid Support | |
| h2o.cosh | Compute the hyperbolic cosine of x | |
| h2o.dayOfWeek | Convert Milliseconds to Day of Week in H2O Datasets | |
| h2o.skewness | Skewness of a column | |
| h2o.impute | Basic Imputation of H2O Vectors | |
| h2o.init | Initialize and Connect to H2O | |
| h2o.hour | Convert Milliseconds to Hour of Day in H2O Datasets | |
| h2o.import_sql_table | Import SQL Table into H2O | |
| h2o.listTimezones | List all of the Time Zones Acceptable by the H2O cluster. | |
| h2o.list_api_extensions | List registered API extensions | |
| h2o.import_sql_select | Import SQL table that is result of SELECT SQL query into H2O | |
| h2o.list_all_extensions | List all H2O registered extensions | |
| h2o.levels | Return the levels from the column requested column. | |
| h2o.hit_ratio_table | Retrieve the Hit Ratios | |
| h2o.mae | Retrieve the Mean Absolute Error Value | |
| h2o.interaction | Categorical Interaction Feature Creation in H2O | |
| h2o.makeGLMModel | Set betas of an existing H2O GLM Model | |
| h2o.dct | Compute DCT of an H2OFrame | |
| h2o.downloadCSV | Download H2O Data to Disk | |
| h2o.download_model | Download the model in binary format. The owner of the file saved is the user by which python session was executed. | |
| h2o.gainsLift | Access H2O Gains/Lift Tables | |
| h2o.glm | Fit a generalized linear model | |
| 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.getModel | Get an R reference to an H2O model | |
| h2o.gam | Fit a General Additive Model | |
| h2o.isnumeric | Check if numeric | |
| h2o.merge | Merge Two H2O Data Frames | |
| h2o.splitFrame | Split an H2O Data Set | |
| h2o.kurtosis | Kurtosis of a column | |
| h2o.kolmogorov_smirnov | Kolmogorov-Smirnov metric for binomial models | |
| h2o.glrm | Generalized low rank decomposition of an H2O data frame | |
| h2o.mojo_predict_csv | H2O Prediction from R without having H2O running | |
| h2o.metric | H2O Model Metric Accessor Functions | |
| h2o.head | Return the Head or Tail of an H2O Dataset. | |
| h2o.month | Convert Milliseconds to Months in H2O Datasets | |
| h2o.mojo_predict_df | H2O Prediction from R without having H2O running | |
| h2o.isolationForest | Trains an Isolation Forest model | |
| h2o.nacnt | Count of NAs per column | |
| h2o.na_omit | Remove Rows With NAs | |
| h2o.hist | Compute A Histogram | |
| h2o.stopLogging | Stop Writing H2O R Logs | |
| h2o.svd | Singular value decomposition of an H2O data frame using the power method | |
| h2o.str | Display the structure of an H2OFrame object | |
| h2o.killMinus3 | Dump the stack into the JVM's stdout. | |
| h2o.list_core_extensions | List registered core extensions | |
| h2o.mse | Retrieves Mean Squared Error Value | |
| h2o.list_jobs | Return list of jobs performed by the H2O cluster | |
| h2o.targetencoder | Transformation of a categorical variable with a mean value of the target variable | |
| h2o.target_encode_transform | Deprecated API. Please use h2o.targetencoder model instead. Transform Frame by Target Encoding Map | |
| h2o.table | Cross Tabulation and Table Creation in H2O | |
| h2o.openLog | View H2O R Logs | |
| h2o.quantile | Quantiles of H2O Frames. | |
| h2o.parseRaw | H2O Data Parsing | |
| h2o.psvm | Trains a Support Vector Machine model on an H2O dataset | |
| h2o.which | Which indices are TRUE? | |
| 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.range | Returns a vector containing the minimum and maximum of all the given arguments. | |
| h2o.which_max | Which indice contains the max value? | |
| h2o.num_iterations | Retrieve the number of iterations. | |
| h2o.kmeans | Performs k-means clustering on an H2O dataset | |
| h2o.rm | Delete Objects In H2O | |
| h2o.melt | Converts a frame to key-value representation while optionally skipping NA values. Inverse operation to h2o.pivot. | |
| h2o.lstrip | Strip set from left | |
| h2o.log1p | Compute the log1p of x | |
| h2o.log2 | Compute the log2 of x | |
| h2o.ls | List Keys on an H2O Cluster | |
| h2o.median | H2O Median | |
| plot.H2OModel | Plot an H2O Model | |
| plot.H2OTabulate | Plot an H2O Tabulate Heatmap | |
| h2o.networkTest | View Network Traffic Speed | |
| h2o.nlevels | Get the number of factor levels for this frame. | |
| h2o.make_metrics | Create Model Metrics from predicted and actual values in H2O | |
| h2o.saveModelDetails | Save an H2O Model Details | |
| h2o.rmse | Retrieves Root Mean Squared Error Value | |
| h2o.rapids | Execute a Rapids expression. | |
| h2o.residual_deviance | Retrieve the residual deviance | |
| h2o.residual_dof | Retrieve the residual degrees of freedom | |
| h2o.rbind | Combine H2O Datasets by Rows | |
| h2o.num_valid_substrings | Count of substrings >= 2 chars that are contained in file | |
| h2o.save_mojo | Save an H2O Model Object as Mojo to Disk | |
| h2o.match | Value Matching in H2O | |
| h2o.nchar | String length | |
| h2o.ncol | Return the number of columns present in x. | |
| h2o.prod | Return the product of all the values present in its arguments. | |
| h2o.show_progress | Enable Progress Bar | |
| h2o.startLogging | Start Writing H2O R Logs | |
| h2o.shutdown | Shut Down H2O Instance | |
| h2o.saveMojo | Deprecated - use h2o.save_mojo instead. Save an H2O Model Object as Mojo to Disk | |
| h2o.no_progress | Disable Progress Bar | |
| h2o.nrow | Return the number of rows present in x. | |
| h2o.proj_archetypes | Convert Archetypes to Features from H2O GLRM Model | |
| h2o.topN | H2O topN | |
| h2o.signif | Round doubles/floats to the given number of significant digits. | |
| h2o.save_to_hive | Save contents of this data frame into a Hive table | |
| h2o.sin | Compute the sine of x | |
| h2o.summary | Summarizes the columns of an H2OFrame. | |
| h2o.transform,H2OWordEmbeddingModel-method | Transform words (or sequences of words) to vectors using a word2vec model. | |
| h2o.sum | Compute the frame's sum by-column (or by-row). | |
| h2o.tot_withinss | Get the total within cluster sum of squares. | |
| h2o.reconstruct | Reconstruct Training Data via H2O GLRM Model | |
| h2o.std_coef_plot | Plot Standardized Coefficient Magnitudes | |
| h2o.tabulate | Tabulation between Two Columns of an H2OFrame | |
| h2o.relevel | Reorders levels of an H2O factor, similarly to standard R's relevel. | |
| h2o.rmsle | Retrieve the Root Mean Squared Log Error | |
| h2o.totss | Get the total sum of squares. | |
| h2o.transform_word2vec | Transform words (or sequences of words) to vectors using a word2vec model. | |
| h2o.tan | Compute the tangent of x | |
| h2o.toupper | Convert strings to uppercase | |
| h2o.trim | Trim Space | |
| h2o.which_min | Which index contains the min value? | |
| h2o.transform | Use H2O Transformation model and apply the underlying transformation | |
| h2o.withinss | Get the Within SS | |
| h2o.word2vec | Trains a word2vec model on a String column of an H2O data frame | |
| h2o.varimp_plot | Plot Variable Importances | |
| h2o.xgboost | Build an eXtreme Gradient Boosting model | |
| h2o.randomForest | Build a Random Forest model | |
| h2o.pivot | Pivot a frame | |
| h2o.runif | Produce a Vector of Random Uniform Numbers | |
| h2o.r2 | Retrieve the R2 value | |
| h2o.performance | Model Performance Metrics in H2O | |
| h2o.rstrip | Strip set from right | |
| h2o.scale | Scaling and Centering of an H2OFrame | |
| h2o.setTimezone | Set the Time Zone on the H2O cluster | |
| h2o.scoreHistory | Retrieve Model Score History | |
| h2o.set_s3_credentials | Creates a new Amazon S3 client internally with specified credentials. | |
| 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.) | |
| is.numeric | Check if numeric | |
| use.package | Use optional package | |
| is.h2o | Is H2O Frame object | |
| staged_predict_proba.H2OModel | Predict class probabilities at each stage of an H2O Model | |
| str.H2OFrame | Display the structure of an H2OFrame object | |
| walking | Muscular Actuations for Walking Subject | |
| length,H2OTree-method | Overrides the behavior of length() function on H2OTree class. Returns number of nodes in an H2OTree | |
| names.H2OFrame | Column names of an H2OFrame | |
| h2o.round | Round doubles/floats to the given number of decimal places. | |
| h2o.sub | String Substitute | |
| prostate | Prostate Cancer Study | |
| zzz | Shutdown H2O cluster after examples run | |
| range.H2OFrame | Range of an H2O Column | |
| h2o.target_encode_create | Create Target Encoding Map | |
| h2o.substring | Substring | |
| h2o.scoreHistoryGAM | Retrieve GLM Model Score History buried in GAM model | |
| h2o.sd | Standard Deviation of a column of data. | |
| h2o.sdev | Retrieve the standard deviations of principal components | |
| h2o.setLevels | Set Levels of H2O Factor Column | |
| h2o.sqrt | Compute the square root of x | |
| h2o.target_encode_fit | Deprecated API. Please use h2o.targetencoder model instead. | |
| h2o.stackedEnsemble | Builds a Stacked Ensemble | |
| h2o.transform,H2OTargetEncoderModel-method | Applies target encoding to a given dataset | |
| h2o.tolower | Convert strings to lowercase | |
| h2o.tokenize | Tokenize String | |
| h2o.train_segments | H2O Segmented-Data Bulk Model Training | |
| h2o.tf_idf | Computes TF-IDF values for each word in given documents. | |
| h2o.trunc | Truncate values in x toward 0 | |
| h2o.toFrame | Convert a word2vec model into an H2OFrame | |
| h2o.week | Convert Milliseconds to Week of Week Year in H2O Datasets | |
| h2o.weights | Retrieve the respective weight matrix | |
| housevotes | United States Congressional Voting Records 1984 | |
| iris | Edgar Anderson's Iris Data | |
| predict.H2OModel | Predict on an H2O Model | |
| predict.H2OAutoML | Predict on an AutoML object | |
| h2o.unique | H2O Unique | |
| print.H2OTable | Print method for H2OTable objects | |
| summary,H2OCoxPHModel-method | Summary method for H2OCoxPHModel objects | |
| h2o.year | Convert Milliseconds to Years in H2O Datasets | |
| print.H2OFrame | Print An H2OFrame | |
| summary,H2OAutoML-method | Format AutoML object in user-friendly way | |
| h2o.xgboost.available | Determines whether an XGBoost model can be built | |
| summary,H2OGrid-method | Format grid object in user-friendly way | |
| summary,H2OModel-method | Print the Model Summary | |
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Details
| Type | Package |
| Date | 2020-09-03 |
| 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' 'gam.R' 'gbm.R' 'generic.R' 'glm.R' 'glrm.R' 'pca.R' 'svd.R' 'psvm.R' 'deeplearning.R' 'stackedensemble.R' 'xgboost.R' 'randomforest.R' 'naivebayes.R' 'word2vec.R' 'w2vutils.R' 'locate.R' 'grid.R' 'segment.R' 'predict.R' 'zzz.R' 'tf-idf.R' |
| RoxygenNote | 7.1.1 |
| Packaged | 2020-09-03 18:54:33 UTC; jenkins |
| Repository | CRAN |
| Date/Publication | 2020-09-12 06:10:04 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 |
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