A B C D E F G H I K L M N O P Q R S T U
| AdditiveModelForecast | AdditiveModelForecast |
| AffinityPropagation | Affinity Propagation |
| AgglomerateHierarchical | Agglomerate Hierarchical Clustering |
| Apriori | Apriori algorithm for association rule mining |
| AprioriLite | Lite Apriori algorithm for association rule mining |
| Arima | Autoregressive Integrated Moving Average |
| Auc | Area Under Curve (AUC) |
| AutoArima | AutoArima |
| BrownExponentialSmoothing | BrownExponentialSmoothing |
| Confusion.matrix | Confusion Matrix |
| confusion.matrix | Confusion Matrix |
| ConnectionContext | ConnectionContext |
| ConvertToHANADataFrame | ConvertToHANADataFrame |
| CovarianceMatrix | Computes covariance matrix |
| CPD | Change-point Detection |
| CRF | Conditional Random Field |
| Croston | Croston |
| DataFrame | hanaml DataFrame |
| DataManipulation | DataManipulation |
| DBSCAN | DBSCAN (Density-Based Spatial Clustering of Applications with Noise) |
| DecisionTreeClassifier | Decision Tree Model for Regression |
| DecisionTreeRegressor | Decision Tree Model for Regression |
| Discretize | Discretize |
| DiscriminantAnalysis | Linear Discriminant Analysis |
| ExponentialRegression | Exponential Regression |
| FeatureNormalizer | Feature Normalizer |
| FPGrowth | FP-Growth algorithm for association rule mining |
| GaussianMixture | Gaussian Mixture Model (GMM) |
| GeoDBSCAN | Geometry DBSCAN |
| GeometricRegression | Bi-variate Geometric Regression |
| GetColumns | GetColumns |
| Glm | Generalized Linear Model |
| hanaml.AccuracyMeasure | Accuracy Measure |
| hanaml.AdditiveModelForecast | AdditiveModelForecast |
| hanaml.AffinityPropagation | Affinity Propagation |
| hanaml.AgglomerateHierarchical | Agglomerate Hierarchical Clustering |
| hanaml.Apriori | Apriori algorithm for association rule mining |
| hanaml.AprioriLite | Lite Apriori algorithm for association rule mining |
| hanaml.Arima | Autoregressive Integrated Moving Average |
| hanaml.Auc | Area Under Curve (AUC) |
| hanaml.AutoArima | AutoArima |
| hanaml.AutoExponentialSmoothing | AutoExponentialSmoothing |
| hanaml.bernoulli | Bernoulli Distribution Sampling |
| hanaml.beta | Beta Distribution Sampling |
| hanaml.binomial | binomial Distribution Sampling |
| hanaml.BrownExponentialSmoothing | BrownExponentialSmoothing |
| hanaml.Cauchy | Cauchy Distribution Sampling |
| hanaml.ChisqGoF | ChisqGoF |
| hanaml.ChisqIndependence | ChisqIndependence |
| hanaml.chisquared | Chisquared Distribution Sampling |
| hanaml.ConditionIndex | Condition Index |
| hanaml.Confusion.matrix | Confusion Matrix |
| hanaml.ConnectionContext | ConnectionContext |
| hanaml.Correlation | Correlation |
| hanaml.CovarianceMatrix | Computes covariance matrix |
| hanaml.CPD | Change-point Detection |
| hanaml.CRF | Conditional Random Field |
| hanaml.Croston | Croston |
| hanaml.DataFrame | hanaml DataFrame |
| hanaml.DBSCAN | DBSCAN (Density-Based Spatial Clustering of Applications with Noise) |
| hanaml.DecisionTreeClassifier | Decision Tree Model for Regression |
| hanaml.DecisionTreeRegressor | Decision Tree Model for Regression |
| hanaml.Discretize | Discretize |
| hanaml.DiscriminantAnalysis | Linear Discriminant Analysis |
| hanaml.DoubleExponentialSmoothing | DoubleExponentialSmoothing |
| hanaml.exponential | Exponential Distribution Sampling |
| hanaml.ExponentialRegression | Exponential Regression |
| hanaml.FeatureNormalizer | Feature Normalizer |
| hanaml.FFT | FastFourierTransform(FFT) |
| hanaml.fisher.f | fisher.f Distribution Sampling |
| hanaml.FPGrowth | FP-Growth algorithm for association rule mining |
| hanaml.gamma | Gamma Distribution Sampling |
| hanaml.GaussianMixture | Gaussian Mixture Model (GMM) |
| hanaml.GeoDBSCAN | Geometry DBSCAN |
| hanaml.geometric | Geometric Distribution Sampling |
| hanaml.GeometricRegression | Bi-variate Geometric Regression |
| hanaml.Glm | Generalized Linear Model |
| hanaml.gumbel | Gumbel Distribution Sampling |
| hanaml.HGBTClassifier | Hybrid Gradient Boosting Tree Classifier |
| hanaml.HGBTRegressor | Hybrid Gradient Boosting Tree Regressor |
| hanaml.HierarchicalForecast | Hierarchical Forecast |
| hanaml.Imputer | Imputer |
| hanaml.IQR | The Interquartile Range |
| hanaml.Kmeans | Kmeans |
| hanaml.Kmedian | K-Medians |
| hanaml.Kmedoid | K-Medoids |
| hanaml.Knn | K-Nearest Neighbor(KNN) |
| hanaml.KNNClassifier | K-Nearest Neighbor(KNN) Classifier |
| hanaml.KNNRegressor | K-Nearest Neighbor(KNN) Regressor |
| hanaml.Kord | KORD algorithm for association rule mining |
| hanaml.LatentDirichletAllocation | Latent Dirichlet Allocation |
| hanaml.LinearRegression | Linear Regression |
| hanaml.LinkPredict | Link Prediction |
| hanaml.LogarithmicRegression | Bi-variate Natural Logarithmic Regression |
| hanaml.LogisticRegression | Logistic Regression |
| hanaml.lognormal | Lognormal Distribution Sampling |
| hanaml.LRSeasonalAdjust | Linear Regression with Damped Trend and Seasonal Adjust |
| hanaml.MDS | Multi-dimensional Scaling |
| hanaml.MLPClassifier | Multi-layer perceptron (MLP) Classifier |
| hanaml.MLPRegressor | Multi-layer perceptron (MLP) Regressor |
| hanaml.ModelStorage | ModelStorage |
| hanaml.MulticlassAuc | Area Under Curve with Multi-class |
| hanaml.Multinomial | Multinomial Distribution |
| hanaml.NaiveBayes | Naive Bayes |
| hanaml.negative.binomial | negative.binomial Distribution Sampling |
| hanaml.normal | Normal Distribution Sampling |
| hanaml.OneClassSVM | OneClassSVM |
| hanaml.OnewayAnova | One-way Analysis of variance (ANOVA) |
| hanaml.OnewayAnovaRepeated | Oneway Repeated Analysis of variance (ANOVA) |
| hanaml.PageRank | Page Rank |
| hanaml.Partition | Partition |
| hanaml.PCA | principal component analysis (PCA) |
| hanaml.PearsonrMatrix | Computes correlation matrix using Pearsonr |
| hanaml.PERT | PERT Distribution Sampling |
| hanaml.Poisson | Poisson Distribution Sampling |
| hanaml.poisson | Poisson Distribution Sampling |
| hanaml.PolynomialRegression | Polynomial Regression |
| hanaml.RandomForestClassifier | Random Forest for Classification |
| hanaml.RandomForestRegressor | Random Forest for Regression |
| hanaml.Sampling | Sampling |
| hanaml.SeasonalDecompose | Seasonality Test |
| hanaml.SingleExponentialSmoothing | Single Exponential Smoothing |
| hanaml.SOM | Self-Organizing Maps |
| hanaml.SPM | sequential pattern mining (SPM) |
| hanaml.student.t | Student's t Distribution Sampling |
| hanaml.SVC | Support Vector Classification (SVC) |
| hanaml.SVR | Support Vector Regression (SVR) |
| hanaml.SVRanking | Support Vector Ranking |
| hanaml.TrendTest | Trend Test |
| hanaml.TripleExponentialSmoothing | TripleExponentialSmoothing |
| hanaml.TTest1Samp | Sample TTest |
| hanaml.TTestInd | Independent sample TTest |
| hanaml.TTestPaired | Paired sample TTest |
| hanaml.uniform | Uniform Distribution Sampling |
| hanaml.UnivariateAnalysis | Univariate Analysis |
| hanaml.VarianceTest | Variance Test |
| hanaml.weibull | weibull Distribution Sampling |
| hanaml.WhiteNoiseTest | White Noise Test |
| HGBTClassifier | Hybrid Gradient Boosting Tree Classifier |
| HGBTRegressor | Hybrid Gradient Boosting Tree Regressor |
| HierForecast | Hierarchical Forecast |
| Imputer | Imputer |
| Kmeans | Kmeans |
| Kmedian | K-Medians |
| Kmedoid | K-Medoids |
| Knn | K-Nearest Neighbor(KNN) |
| KNNClassifier | K-Nearest Neighbor(KNN) Classifier |
| KNNRegressor | K-Nearest Neighbor(KNN) Regressor |
| Kord | KORD algorithm for association rule mining |
| LatentDirichletAllocation | Latent Dirichlet Allocation |
| LinearRegression | Linear Regression |
| LinkPredict | Link Prediction |
| LogarithmicRegression | Bi-variate Natural Logarithmic Regression |
| LogisticRegression | Logistic Regression |
| MLPClassifier | Multi-layer perceptron (MLP) Classifier |
| MLPRegressor | Multi-layer perceptron (MLP) Regressor |
| ModelStorage | ModelStorage |
| MulticlassAuc | Area Under Curve with Multi-class |
| NaiveBayes | Naive Bayes |
| OneClassSVM | OneClassSVM |
| PageRank | Page Rank |
| PCA | principal component analysis (PCA) |
| PearsonrMatrix | Computes correlation matrix using Pearsonr |
| PolynomialRegression | Polynomial Regression |
| predict.AdditiveModelForecast | Make Predictions from a "AdditiveModelForecast" Object |
| predict.Arima | Make Predictions from a "Arima" Object |
| predict.AutoArima | Make Predictions from a "AutoArima" Object |
| predict.CRF | Make Predictions from a CRF Object |
| predict.DBSCAN | Make Predictions from a "DBSCAN" Object |
| predict.DecisionTreeClassifier | Predict based on model for Decision Tree Classifier |
| predict.DecisionTreeRegressor | Predict based on model for Decision Tree Regressor |
| predict.DiscriminantAnalysis | Make Predictions from a Linear Discriminant Analysis Object |
| predict.ExponentialRegression | Make Predictions from a "ExponentialRegression" Object |
| predict.GaussianMixture | Make Predictions from a GaussianMixture Object |
| predict.GeometricRegression | Make Predictions from a "GeometricRegression" Object |
| predict.Glm | Make Predictions from a "Glm" Object |
| predict.HGBTClassifier | Predict using HGBTClassifier |
| predict.HGBTRegressor | Predict using HGBTRegressor |
| predict.Kmeans | Make Predictions from a "Kmeans" Object |
| predict.Knn | Make Predictions from a "Knn" Object |
| predict.KNNClassifier | Make Predictions from a "KNNClassifier" Object |
| predict.KNNRegressor | Make Predictions from a "KNNRegressor" Object |
| predict.LinearRegression | Make Predictions from a "LinearRegression" Object |
| predict.LogarithmicRegression | Make Predictions from a "LogarithmicRegression" Object |
| predict.LogisticRegression | Make Predictions from a "LogisticRegression" Object |
| predict.MLPClassifier | MLP Classifier Prediction: |
| predict.MLPRegressor | Predict using MLP Regressor |
| predict.NaiveBayes | Make Predictions from a "NaiveBayes" Object |
| predict.OneClassSVM | Make Predictions from a "OneClassSVM" Object |
| predict.PolynomialRegression | Make Predictions from a "PolynomialRegression" Object |
| predict.RandomForestClassifier | Predict based on model for Random Forest Classifier |
| predict.RandomForestRegressor | Predict based on model for Random Forest Regressor |
| predict.SOM | Make Predictions from a "SOM" Object |
| predict.SVC | Make Predictions from a "SVC" Object |
| predict.SVR | Make Predictions from a "SVR" Object |
| predict.SVRanking | Make Predictions from a "SVRanking" Object |
| QuoteName | QuoteName |
| RandomForestClassifier | Random Forest for Classification |
| RandomForestRegressor | Random Forest for Regression |
| SOM | Self-Organizing Maps |
| SPM | sequential pattern mining (SPM) |
| SVC | Support Vector Classification (SVC) |
| SVR | Support Vector Regression (SVR) |
| SVRanking | Support Vector Ranking |
| transform.Discretize | Make transform from a "Discretize" Object |
| transform.DiscriminantAnalysis | Make Projections from a Linear Discriminant Analysis Object |
| transform.FeatureNormalizer | Make Transform from a "FeatureNormalizer" Object |
| transform.Imputer | Make transformation from a "Imputer" Object |
| transform.LatentDirichletAllocation | Make Inference from a "LatentDirichletAllocation" Object |
| transform.PCA | Make Projection from a "PCA" Object |
| TripleExponentialSmoothing | TripleExponentialSmoothing |
| TTest1Samp | Sample TTest |
| UnivariateAnalysis | Univariate Analysis |