The node creates a Bayesian model from the given training data. It calculates the number of rows per attribute value per class for nominal attributes and the Gaussian distribution for numerical attributes. The created model could be used in the naive Bayes predictor to predict the class membership of unclassified data. The node displays a warning message if any columns are ignored due to unsupported data types. For example Bit Vector columns are ignored when the PMML compatibility flag is enabled since they are not supported by the PMML standard.
Options
Popular Predecessors
- Partitioning20 %
Scorer6 %Excel Reader (XLS)3 %- Column Filter3 %
- X-Partitioner3 %
Number To String3 %- Number to String2 %
- Equal Size Sampling1 %
- Feature Selection Loop Start (1:1)1 %
- Normalizer1 %
- Excel Reader1 %
- SMOTE1 %
- CSV Reader1 %
File Reader1 %Table Row to Variable1 %- Naive Bayes Predictor1 %
- Parameter Optimization Loop Start< 1 %
- Correlation Filter< 1 %
- CAIM Binner< 1 %
- Document Vector< 1 %
- Table Reader< 1 %
- Table View (JavaScript)< 1 %
- Column Appender< 1 %
CSV Reader< 1 %- Table Creator< 1 %
- Naive Bayes Learner< 1 %
- Domain Calculator< 1 %
- Rule-based Row Filter< 1 %
- Statistics< 1 %
- String Manipulation< 1 %
- Parameter Optimization Loop End< 1 %
- Feature Selection Filter< 1 %
- k-Means< 1 %
- Random Forest Learner< 1 %
- Numeric Binner< 1 %
- One to Many< 1 %
Linear Correlation< 1 %Column Rename< 1 %- Color Manager< 1 %
- Boosting Learner Loop Start< 1 %
- Missing Value (Apply)< 1 %
- X-Aggregator< 1 %
- Logistic Regression Learner< 1 %
- Scorer< 1 %
- PCA< 1 %
String To Number< 1 %- Constant Value Column< 1 %
- Duplicate Row Filter< 1 %
- Number to String (PMML)< 1 %
- Table Transposer< 1 %
- Value Counter< 1 %
- Rule Engine< 1 %
Extract Date&Time Fields< 1 %- Logistic Regression Predictor< 1 %
- Reference Column Filter< 1 %
- Table Manipulator< 1 %
- Denormalizer< 1 %
- Crosstab< 1 %
- Scorer (JavaScript)< 1 %
- Generic Loop Start< 1 %
- String to Path< 1 %
- Decision Tree Predictor< 1 %
- GroupBy< 1 %
- Shuffle< 1 %
- Scatter Plot (JavaScript)< 1 %
- ARFF Reader< 1 %
- Feature Selection Loop Start (2:2)< 1 %
- Linear Regression Learner< 1 %
- Random Forest Predictor< 1 %
- Concatenate< 1 %
- Auto-Binner< 1 %
- Bootstrap Sampling< 1 %
- Category to Number< 1 %
- Number to Category (Apply)< 1 %
- String to Number< 1 %
Column Appender< 1 %- Missing Value Column Filter< 1 %
- Nominal Value Row Filter< 1 %
Row Splitter (deprecated)< 1 %Row Filter (deprecated)< 1 %- Normalizer (Apply)< 1 %
- Missing Value< 1 %
- Normalizer (PMML)< 1 %
- Row Sampling< 1 %
- Sorter< 1 %
- String Replacer< 1 %
- Numeric Outliers< 1 %
- ROC Curve (legacy)< 1 %
- Category to Class< 1 %
- Bag Of Words Creator< 1 %
- Document Vector Applier< 1 %
- Column Selection (legacy)< 1 %
- Decision Tree View (JavaScript)< 1 %
- Line Plot (JavaScript)< 1 %
- Table Row to Variable< 1 %
- File Reader< 1 %
- K Nearest Neighbor< 1 %
- Column Resorter< 1 %
- Joiner< 1 %
- Data Explorer< 1 %
- ROC Curve (JavaScript)< 1 %
- List Files/Folders< 1 %
- MolImporter< 1 %
Table Row to Variable< 1 %- Cluster Assigner< 1 %
- PCA Apply< 1 %
Joiner< 1 %String Replace (Dictionary)< 1 %- Weka Predictor (3.7)< 1 %
- UNIX Timestamp to Date&Time< 1 %
- Enrichment Analyzer< 1 %
Rank Correlation< 1 %- Java Snippet< 1 %
- PNN Learner (DDA)< 1 %
- SVM Predictor< 1 %
- Nominal Value Row Splitter< 1 %
- Reference Row Filter< 1 %
Excel Reader (XLS)< 1 %Read Excel Sheet Names (XLS)< 1 %- TF< 1 %
JSON Reader< 1 %Python Script (1⇒1)< 1 %- Chunk Loop Start< 1 %
- CASE Switch Start< 1 %
- Create Collection Column< 1 %
Table Row To Variable Loop Start< 1 %Table Reader< 1 %- Fuzzy c-Means< 1 %
- Decision Tree Learner< 1 %
Numeric Scorer< 1 %- Pivot< 1 %
Number To String (PMML)< 1 %- Column Splitter< 1 %
- Data Generator< 1 %
- Enrichment Plotter (legacy)< 1 %
- Lift Chart (legacy)< 1 %
- Math Formula< 1 %
- Java Snippet (simple)< 1 %
- Java Edit Variable (simple)< 1 %
- Document Data Extractor< 1 %
- String to Date&Time< 1 %
- Fuzzy Rule Predictor< 1 %
- CASE Switch End< 1 %
- Benchmark Start (Memory Monitoring)< 1 %
- Outlier Removal< 1 %
- Active Learn Loop Start (Legacy)< 1 %
- Active Learning Loop Start< 1 %
- Split Collection Column< 1 %
- Try (Data Ports)< 1 %
Database Reader< 1 %Database Pivot< 1 %- Feature Selection Loop End< 1 %
Counting Loop Start< 1 %- Column List Loop Start< 1 %
Generic Loop Start< 1 %- MultiLayerPerceptron Predictor< 1 %
PCA Apply< 1 %PCA< 1 %- Regression Predictor< 1 %
- Numeric Scorer< 1 %
- PCA Compute< 1 %
- Tree Ensemble Learner< 1 %
Concatenate (Optional in)< 1 %- Auto-Binner (Apply)< 1 %
- Expand Bit Vector< 1 %
- Column Combiner< 1 %
- Column Comparator< 1 %
- Column Aggregator< 1 %
- Column Renamer (Dictionary)< 1 %
- Linear Correlation< 1 %
- Cross Joiner< 1 %
- CAIM Applier< 1 %
- Edit Nominal Domain< 1 %
- Extract Missing Value Cause< 1 %
- Filter Apply< 1 %
- Filter Apply Row Splitter< 1 %
- HiLite Row Splitter< 1 %
- Column Filter (PMML)< 1 %
- Normalizer Apply (PMML)< 1 %
String To Number (PMML)< 1 %- String to Number (PMML)< 1 %
- Rule-based Row Splitter< 1 %
- One-way ANOVA< 1 %
- End IF< 1 %
- IF Switch< 1 %
- Extract Table Dimension< 1 %
- DB Reader< 1 %
- DB Query Reader< 1 %
- DB Writer< 1 %
- k-Medoids< 1 %
- K Nearest Neighbor (Distance Function)< 1 %
- Variable Expressions< 1 %
- Math Formula (Multi Column)< 1 %
- Radar Plot Appender< 1 %
- Word Vector Apply (legacy)< 1 %
- Frequency Filter< 1 %
- IDF< 1 %
- Dictionary Filter< 1 %
- PDF Parser< 1 %
- Document Vector Hashing< 1 %
- Column Filter (legacy)< 1 %
- Lift Chart (JavaScript)< 1 %
- Table Editor (JavaScript)< 1 %
- Container Input (Table)< 1 %
- JSON Path< 1 %
- Date&Time-based Row Filter< 1 %
- Modify Date< 1 %
- Moving Average< 1 %
- Fingerprints< 1 %
- Run Garbage Collector< 1 %
- R Snippet< 1 %
- Strings to Binary Objects< 1 %
- Catch Errors (Data Ports)< 1 %
- PNN Predictor< 1 %
- Hierarchical Clustering< 1 %
- RProp MLP Learner< 1 %
- Association Rule Learner< 1 %
- Binner (Dictionary)< 1 %
- Create Bit Vector< 1 %
- Double to Integer< 1 %
- Row Filter (Labs)< 1 %
- Low Variance Filter< 1 %
- Numeric Row Splitter< 1 %
- Rule-based Row Filter (Dictionary)< 1 %
- Cronbach Alpha< 1 %
- Rank Correlation< 1 %
- Linear Discriminant Analysis< 1 %
- Cache< 1 %
- HiLite Table (legacy)< 1 %
- Box Plot (legacy)< 1 %
- Similarity Search< 1 %
- Boosting Learner Loop End< 1 %
- Model to Cell< 1 %
- Strings to Document< 1 %
- Term Vector< 1 %
- Path to String< 1 %
- RDKit Descriptor Calculation< 1 %
- RDKit Interactive Table< 1 %
Views
- Naive Bayes Learner View
- The view displays the learned model with the number of rows per class attribute. The number of rows per attribute per class for nominal attributes and the Gaussian distribution per class for numerical attributes.
Workflows
!Modern UI_ABC-XYX-RFM AutoML SuperstoreKNIME Hub- 0_install_AI_extensionsKNIME Hub
- 01_AutoML_Component_via_Interactive_ViewsKNIME Hub
- 01_Combining_Classifiers_using_Prediction_FusionKNIME Hub
- 01_Explainable_Artificial_Intelligence_(XAI)_SimpleKNIME Hub
- Show all 368 workflows
Links
- Export PMML that outputs class probabilitiesby mlauber71 on 2019-01-22forum.knime.com/p/53278
- Help!- Churn for Bank Customers Analyzingby gonhaddock on 2022-05-18forum.knime.com/p/157353
Developers
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.