Python Client API for machine learning algorithms

Contents:
- Python Machine Learning Client for SAP HANA
- Installation Guide
- hana-ml Tutorials
- Changelog
- What's New and Changed in version 2.13.220722
- What's New and Changed in version 2.13.220715
- What's New and Changed in version 2.13.220701
- What's New and Changed in version 2.13.220608
- What's New and Changed in version 2.13.220511
- What's New and Changed in version 2.12.220428
- What's New and Changed in version 2.12.220425
- What's New and Changed in version 2.12.220408
- What's New and Changed in version 2.12.220325
- What's New and Changed in version 2.11.220209
- What's New and Changed in version 2.11.220107
- What's New and Changed in version 2.11.211211
- What's New and Changed in version 2.10.210918
- What's New and Changed in version 2.9.210726
- What's New and Changed in version 2.9.210709
- What's New and Changed in version 2.9.210630
- What's New and Changed in version 2.9.210619
- What's New and Changed in version 2.8.210421
- What's New and Changed in version 2.8.210321
- What's New and Changed in version 2.6.210126
- What's New and Changed in version 2.6.210113
- What's New and Changed in version 2.6.201209
- What's New and Changed in version 2.6.201106
- What's New and Changed in version 2.6.201016(2.6.200928)
- What's New and Changed in version 2.5.200626
- What's New and Changed in version 1.0.8
- hana_ml.dataframe
- hana_ml.algorithms.apl package
- hana_ml.algorithms.pal package
- hana_ml.algorithms.pal.abc_analysis
- hana_ml.algorithms.pal.association
- hana_ml.algorithms.pal.clustering
- hana_ml.algorithms.pal.crf
- hana_ml.algorithms.pal.decomposition
- hana_ml.algorithms.pal.decomposition.LatentDirichletAllocation
- hana_ml.algorithms.pal.decomposition.PCA
- hana_ml.algorithms.pal.decomposition.CATPCA
- hana_ml.algorithms.pal.discriminant_analysis
- hana_ml.algorithms.pal.kernel_density
- hana_ml.algorithms.pal.linear_model
- hana_ml.algorithms.pal.linear_model.LinearRegression
- hana_ml.algorithms.pal.linear_model.LogisticRegression
- hana_ml.algorithms.pal.linear_model.OnlineLinearRegression
- hana_ml.algorithms.pal.linear_model.OnlineMultiLogisticRegression
- hana_ml.algorithms.pal.linkpred
- hana_ml.algorithms.pal.metrics
- hana_ml.algorithms.pal.mixture
- hana_ml.algorithms.pal.model_selection
- hana_ml.algorithms.pal.naive_bayes
- hana_ml.algorithms.pal.neighbors
- hana_ml.algorithms.pal.neighbors.KNNClassifier
- hana_ml.algorithms.pal.neighbors.KNNRegressor
- hana_ml.algorithms.pal.neural_network
- hana_ml.algorithms.pal.neural_network.MLPClassifier
- hana_ml.algorithms.pal.neural_network.MLPRegressor
- hana_ml.algorithms.pal.pagerank
- hana_ml.algorithms.pal.partition
- hana_ml.algorithms.pal.pipeline
- hana_ml.algorithms.pal.preprocessing
- hana_ml.algorithms.pal.random
- hana_ml.algorithms.pal.recommender
- hana_ml.algorithms.pal.regression
- hana_ml.algorithms.pal.som
- hana_ml.algorithms.pal.stats
- hana_ml.algorithms.pal.svm
- hana_ml.algorithms.pal.svm.SVC
- hana_ml.algorithms.pal.svm.SVR
- hana_ml.algorithms.pal.svm.SVRanking
- hana_ml.algorithms.pal.svm.OneClassSVM
- hana_ml.algorithms.pal.trees
- hana_ml.algorithms.pal.trees.DecisionTreeClassifier
- hana_ml.algorithms.pal.trees.DecisionTreeRegressor
- hana_ml.algorithms.pal.trees.RDTClassifier
- hana_ml.algorithms.pal.trees.RDTRegressor
- hana_ml.algorithms.pal.trees.HybridGradientBoostingClassifier
- hana_ml.algorithms.pal.trees.HybridGradientBoostingRegressor
- hana_ml.algorithms.pal.tsne
- hana_ml.algorithms.pal.tsa.accuracy_measure
- hana_ml.algorithms.pal.tsa.additive_model_forecast
- hana_ml.algorithms.pal.tsa.arima
- hana_ml.algorithms.pal.tsa.auto_arima
- hana_ml.algorithms.pal.tsa.bsts
- hana_ml.algorithms.pal.tsa.changepoint
- hana_ml.algorithms.pal.tsa.correlation_function
- hana_ml.algorithms.pal.tsa.dtw
- hana_ml.algorithms.pal.tsa.fast_dtw
- hana_ml.algorithms.pal.tsa.fft
- hana_ml.algorithms.pal.tsa.garch
- hana_ml.algorithms.pal.tsa.hierarchical_forecast
- hana_ml.algorithms.pal.tsa.intermittent_forecast
- hana_ml.algorithms.pal.tsa.lr_seasonal_adjust
- hana_ml.algorithms.pal.tsa.lstm
- hana_ml.algorithms.pal.tsa.online_algorithms
- hana_ml.algorithms.pal.tsa.rnn
- hana_ml.algorithms.pal.tsa.seasonal_decompose
- hana_ml.algorithms.pal.tsa.trend_test
- hana_ml.algorithms.pal.tsa.vector_arima
- hana_ml.algorithms.pal.tsa.wavelet
- hana_ml.algorithms.pal.tsa.white_noise_test
- hana_ml.algorithms.pal.unified_classification
- hana_ml.algorithms.pal.wst
- hana_ml.algorithms.pal.unified_regression
- hana_ml.algorithms.pal.unified_clustering
- hana_ml.algorithms.pal.unified_exponentialsmoothing
- hana_ml.algorithms.pal.auto_ml
- hana_ml.algorithms.pal.tsa.stationarity_test
- hana_ml.algorithms.pal.tsa.exponential_smoothing.SingleExponentialSmoothing
- hana_ml.algorithms.pal.tsa.exponential_smoothing.DoubleExponentialSmoothing
- hana_ml.algorithms.pal.tsa.exponential_smoothing.TripleExponentialSmoothing
- hana_ml.algorithms.pal.tsa.exponential_smoothing.AutoExponentialSmoothing
- hana_ml.algorithms.pal.tsa.exponential_smoothing.BrownExponentialSmoothing
- hana_ml.algorithms.pal.tsa.exponential_smoothing.Croston
- hana_ml.algorithms.pal.tsa.exponential_smoothing.CrostonTSB
- hana_ml.visualizers package
- hana_ml.visualizers.eda
- hana_ml.visualizers.metrics
- hana_ml.visualizers.m4_sampling
- hana_ml.visualizers.model_debriefing
- hana_ml.visualizers.dataset_report
- hana_ml.visualizers.shap
- hana_ml.visualizers.unified_report
- hana_ml.visualizers.visualizer_base
- hana_ml.visualizers.digraph
- hana_ml.visualizers.word_cloud
- hana_ml.visualizers.automl_progress
- hana_ml.visualizers.automl_report
- hana_ml.ml_exceptions
- hana_ml.model_storage
- hana_ml.artifacts package
- hana_ml.docstore package
- hana_ml.spatial package
- hana_ml.graph package
- hana_ml.graph.algorithms package
- hana_ml.text.tm package
- FAQs
- Q1 : Which version of hana-ml should I install?
- Q2 : Why do I meet a 'matplotlib' error when I invoke box_plot()?
- Q3 : Why do I meet a error "[WinError 126] The specified module could not be found" when I import hana-ml?
- Q4 : What dependencies are required for hana-ml?
- Q5 : How to solve the garbled Chinese font problem like □□, when I use library 'Matplotlib'?
- Q6 : Why the output of FeatureNormalizer and KBinsDiscretizer is not what I expect? For example, the transformed value is a integer when a float is expected in FeatureNormalizer.
- Q7 : How could I solve the "RuntimeError: Failed to transform image object to string!", when I use UnifiedReport?
- Q8 : How could I solve the issue "KeyError: 'STORAGE_TYPE'" when I use model storage functionalites after I upgrade hana-ml to version 2.9.21XXXX?
- Q9 : Why do I meet a error message like "SAP DBTech JDBC: [328]: invalid name of function or procedure: no procedure with name XXX found:"?
- Q10 : Why do I meet a error "'NoneType' object has no attribute 'connection'" when I use model storage functionality for ARIMA/AutoARIMA in predict function?
- Q11 : Why there is no figure appear when I invoke ShapleyExplainer and its function summary_plot()?
- Q12 : Why an additional figure ( e.g. a confusion matrix) is displayed under each page of a report when I invoke UnifiedReport() to display a model report?
- Q13 : How can I install hana-ml on Mac with new M1 processor because I get "ERROR: Could not find a version that satisfies the requirement hdbcli (from versions: none) and ERROR: No matching distribution found for hdbcli"?
- Q14 : How to manage SAP HANA workload with Workload Classes?