This node uses an existing decision tree (passed in through the model port) to predict the class value for new patterns. The Node can be configured as follows:
Options
Popular Predecessors
- Decision Tree Learner40 %
- Partitioning17 %
Number To String4 %- Column Filter2 %
Database Connection Table Reader1 %- CSV Reader1 %
- X-Partitioner1 %
- Excel Reader1 %
XLS Reader1 %Excel Reader (XLS)1 %- PMML Reader< 1 %
- Number to String< 1 %
Naive Bayes Learner< 1 %- Missing Value (Apply)< 1 %
- Equal Size Sampling< 1 %
- Normalizer (Apply)< 1 %
- File Reader< 1 %
- Model Reader< 1 %
PMML Reader< 1 %- Decision Tree to Ruleset< 1 %
String To Number< 1 %- ARFF Reader< 1 %
Number To String (PMML)< 1 %Color Appender< 1 %- Color Manager< 1 %
- Table Creator< 1 %
Naive Bayes Predictor< 1 %Column Appender< 1 %- Linear Regression Learner< 1 %
K Nearest Neighbor< 1 %- Model Loop Start< 1 %
- Color Appender< 1 %
- Missing Value< 1 %
PCA Apply< 1 %- Logistic Regression Learner< 1 %
- Category to Class< 1 %
- Scorer< 1 %
- Rule Engine< 1 %
- Conditional Box Plot (legacy)< 1 %
Random Forest Learner< 1 %Row Filter (deprecated)< 1 %- Normalizer< 1 %
- Random Forest Learner< 1 %
File Reader< 1 %- RProp MLP Learner< 1 %
Logistic Regression Learner< 1 %Row Splitter (deprecated)< 1 %- Parameter Optimization Loop Start< 1 %
Model Reader< 1 %- Decision Tree Predictor< 1 %
- Chunk Loop Start< 1 %
Linear Correlation< 1 %- Naive Bayes Learner< 1 %
Joiner< 1 %- Joiner< 1 %
- Scorer (JavaScript)< 1 %
- PNN Learner (DDA)< 1 %
PCA< 1 %- CAIM Applier< 1 %
- Math Formula< 1 %
- R to PMML< 1 %
- DB Reader< 1 %
- Column Expressions< 1 %
Scorer< 1 %- Missing Value Column Filter< 1 %
Rank Correlation< 1 %- Box Plot (legacy)< 1 %
- Shape Manager< 1 %
- Fuzzy c-Means< 1 %
- Logistic Regression Predictor< 1 %
- Number to String (PMML)< 1 %
- Correlation Filter< 1 %
- Document Data Extractor< 1 %
- Random Forest Predictor< 1 %
Concatenate (Optional in)< 1 %- Numeric Row Splitter< 1 %
- Sorter< 1 %
- Rule-based Row Filter< 1 %
- Hierarchical Clustering< 1 %
Excel Reader (XLS)< 1 %- Document Vector Hashing Applier< 1 %
- k-Means< 1 %
- Case Converter< 1 %
- Cross Joiner< 1 %
Column Rename< 1 %- Weka Predictor (3.7)< 1 %
- JSON to Table< 1 %
- Extract Time Window (legacy)< 1 %
- Numeric Scorer< 1 %
- Association Rule Learner< 1 %
- SVM Predictor< 1 %
- Interactive Histogram (legacy)< 1 %
- PMML Ensemble Loop End< 1 %
- Math Formula (Multi Column)< 1 %
- File Reader (Complex Format)< 1 %
- Table Reader< 1 %
PMML Reader< 1 %Counting Loop Start< 1 %Regression Predictor< 1 %- SMOTE< 1 %
- SVM Learner< 1 %
- Simple Regression Tree to PMML< 1 %
- Simple Regression Tree Predictor< 1 %
- Concatenate< 1 %
- Numeric Binner< 1 %
- Bootstrap Sampling< 1 %
- Category to Number (Apply)< 1 %
- Number to Category (Apply)< 1 %
- Denormalizer (PMML)< 1 %
- Rule-based Row Splitter< 1 %
JSON Reader< 1 %- Gradient Boosted Trees Predictor< 1 %
- Cell Splitter< 1 %
- Decision Tree View (JavaScript)< 1 %
- Date&Time Difference< 1 %
- Cluster Assigner< 1 %
- Polynomial Regression Learner< 1 %
Random Forest Predictor< 1 %- Auto-Binner (Apply)< 1 %
- Auto-Binner< 1 %
Cell Splitter< 1 %- Category to Number< 1 %
- GroupBy< 1 %
- Denormalizer< 1 %
- RowID< 1 %
- Column Splitter< 1 %
- Statistics< 1 %
- ROC Curve (legacy)< 1 %
- Boosting Learner Loop Start< 1 %
Excel Reader (XLS)< 1 %- Document Vector Applier< 1 %
- Fuzzy Rule Predictor< 1 %
- PNN Predictor< 1 %
- PCA Apply< 1 %
- Tree Ensemble Learner (Regression)< 1 %
- String to Number< 1 %
- IF Switch< 1 %
- Scatter Plot (JavaScript)< 1 %
- PMML Simple Regression Tree Predictor< 1 %
- Table Manipulator< 1 %
- Table Splitter< 1 %
CSV Reader< 1 %Table Reader< 1 %- Feature Selection Filter< 1 %
Loop End< 1 %Variable Loop End< 1 %- X-Aggregator< 1 %
- MultiLayerPerceptron Predictor< 1 %
- Regression Predictor< 1 %
- Random Forest Learner (Regression)< 1 %
- Column Combiner< 1 %
- Column Rename (Regex)< 1 %
- One to Many< 1 %
- Constant Value Column< 1 %
- Domain Calculator< 1 %
- Double to Integer< 1 %
- Reference Column Filter< 1 %
- HiLite Row Splitter< 1 %
- Nominal Value Row Filter< 1 %
- Reference Row Filter< 1 %
- Numeric Binner (PMML)< 1 %
- Normalizer Apply (PMML)< 1 %
- Normalizer (PMML)< 1 %
- Row Sampling< 1 %
- String Manipulation< 1 %
- String Replacer< 1 %
- Target Shuffling< 1 %
- Rule Engine (Dictionary)< 1 %
- Data Explorer< 1 %
Linear Discriminant Analysis< 1 %- Data Generator< 1 %
- Boosting Predictor Loop Start< 1 %
- Table to PMML Ensemble< 1 %
- Cell to PMML< 1 %
Read Excel Sheet Names (XLS)< 1 %- Line Plot (JavaScript)< 1 %
- Table Editor (JavaScript)< 1 %
- Container Input (Table)< 1 %
- RDKit Descriptor Calculation< 1 %
Line Reader< 1 %- Feature Selection Loop Start (1:1)< 1 %
- Naive Bayes Predictor< 1 %
- K Nearest Neighbor< 1 %
- PCA< 1 %
Cell Replacer< 1 %- Column Renamer (Dictionary)< 1 %
- Column Resorter< 1 %
- Linear Correlation< 1 %
- Duplicate Row Filter< 1 %
- Extract Missing Value Cause< 1 %
- Reference Row Splitter< 1 %
- String to Number (PMML)< 1 %
String Replace (Dictionary)< 1 %- Numeric Outliers (Apply)< 1 %
- Numeric Outliers< 1 %
- Capture Workflow Start< 1 %
- SDF Reader< 1 %
- Table View (JavaScript)< 1 %
- SHAP Loop Start< 1 %
- Parameter Optimization Loop End< 1 %
- Column Appender< 1 %
- String Manipulation (Multi Column)< 1 %
- Workflow Executor< 1 %
- Column Renamer< 1 %
Table Row to Variable< 1 %- Group Loop Start< 1 %
- Column Aggregator< 1 %
Document vector< 1 %Python Edit Variable< 1 %- Wait...< 1 %
- Try (Data Ports)< 1 %
Variable to Table Column< 1 %Database Update< 1 %- Fuzzy Rule Learner< 1 %
- SOTA Predictor< 1 %
- Simple Regression Tree Learner< 1 %
- Column Auto Type Cast< 1 %
- Parallel Chunk Start< 1 %
- Boosting Learner Loop End< 1 %
- Information Gain Calculator< 1 %
- PMML Writer< 1 %
- One to Many (PMML)< 1 %
- Extract Table Dimension< 1 %
Backward Feature Elimination Start (2:2)< 1 %Tree Ensemble Learner< 1 %- Table Validator (Reference)< 1 %
- Counter Generation< 1 %
- Conditional Label Assigner< 1 %
- Association Rule Learner (Borgelt)< 1 %
- Document Vector< 1 %
- R Snippet< 1 %
- String to Date&Time< 1 %
- Molecular Properties< 1 %
- String to URI< 1 %
- Tree Ensemble Learner< 1 %
- Column Merger< 1 %
- Table Validator< 1 %
- Interactive Pie chart (legacy)< 1 %
- Term Co-Occurrence Counter< 1 %
Database Reader< 1 %Loop End (2 ports)< 1 %- DBSCAN< 1 %
Numeric Scorer< 1 %Gradient Boosted Trees Predictor< 1 %- Tree Ensemble Predictor< 1 %
- Lag Column< 1 %
- Column Filter (PMML)< 1 %
- Value Counter< 1 %
- Radar Plot Appender< 1 %
Python Script (2⇒1)< 1 %- R Source (Table)< 1 %
- R to Table< 1 %
- Test Data Generator< 1 %
- Catch Errors (Generic Ports)< 1 %
- Fixed Width File Reader< 1 %
- Java Snippet< 1 %
Generic Loop Start< 1 %PCA Compute< 1 %Tree Ensemble Learner< 1 %Gradient Boosted Trees Predictor< 1 %- PMML Validation Data Appender< 1 %
- Row Splitter (Labs)< 1 %
- Number Rounder< 1 %
- Ruleset Predictor< 1 %
- Cache< 1 %
- Timer Info< 1 %
- Lift Chart (legacy)< 1 %
- Scatter Plot (legacy)< 1 %
- Empty Table Creator< 1 %
- Random Boolean Assigner< 1 %
- Boosting Predictor Loop End< 1 %
PMML Predictor< 1 %- Cell to Model< 1 %
- Topic Extractor (Parallel LDA)< 1 %
- POS Tagger< 1 %
Column Filter Configuration< 1 %- Column Filter (legacy)< 1 %
- Value Filter (legacy)< 1 %
- Tag Cloud (JavaScript)< 1 %
- Container Input (Row)< 1 %
- Table to JSON< 1 %
- Date&Time-based Row Filter< 1 %
- Row Filter (Labs)< 1 %
- Frequency Filter< 1 %
- Weka Cluster Assigner (3.7)< 1 %
- Google Analytics Query (legacy)< 1 %
- Moving Average< 1 %
- Indigo Fingerprint< 1 %
- Outlier Removal< 1 %
- Split Collection Column< 1 %
PMML Writer< 1 %Interval Loop Start< 1 %- PMML Model Appender< 1 %
- CAIM Binner< 1 %
- Nominal Value Row Splitter< 1 %
- Low Variance Filter< 1 %
- Shuffle< 1 %
- Table Transposer< 1 %
- Unpivot< 1 %
- Distance Matrix Calculate< 1 %
- k-Medoids< 1 %
- Model Loop End< 1 %
- PMML to Cell< 1 %
Document Data Extractor< 1 %Document Vector Adapter< 1 %Strings To Document< 1 %- Term to String< 1 %
Python Script (1⇒1)< 1 %- GET Request< 1 %
Extract Date&Time Fields< 1 %- String to Date/Time (legacy)< 1 %
- 2D Coordinates< 1 %
- Range Splitter< 1 %
- Fingerprints Expander< 1 %
- Pareto Ranking< 1 %
- Breakpoint< 1 %
- Catch Errors (Var Ports)< 1 %
Table Row To Variable Loop Start< 1 %- Read Images< 1 %
Database Column Filter< 1 %Database Looping< 1 %Database Column Rename< 1 %Parameterized Database Query< 1 %List Files< 1 %Backward Feature Elimination Start (1:1)< 1 %- Feature Selection Loop Start (2:2)< 1 %
- Column List Loop Start< 1 %
Recursive Loop Start (2 ports)< 1 %- Hierarchical Cluster Assigner (local)< 1 %
- Decision Tree to Image< 1 %
- Entropy Scorer< 1 %
Tree Ensemble Model Extract< 1 %- Gradient Boosted Trees Learner (Regression)< 1 %
Tree Ensemble Predictor< 1 %- Tree Ensemble Statistics< 1 %
- Add Empty Rows< 1 %
- Binner (Dictionary)< 1 %
- Create Bit Vector< 1 %
- Expand Bit Vector< 1 %
- Column Comparator< 1 %
- Many to One< 1 %
- Reference Column Splitter< 1 %
- Constant Value Column Filter< 1 %
- Filter Apply< 1 %
- Filter Apply Row Splitter< 1 %
- Interactive HiLite Collector< 1 %
- Pivot< 1 %
- Many to One (PMML)< 1 %
String To Number (PMML)< 1 %- Ruleset Editor< 1 %
- Rule-based Row Filter (Dictionary)< 1 %
- Single sample t-test< 1 %
- Independent groups t-test< 1 %
- Linear Discriminant Analysis< 1 %
CASE Switch Data (End)< 1 %CASE Switch Model (End)< 1 %CASE Switch Data (Start)< 1 %- Crosstab< 1 %
- HiLite Table (legacy)< 1 %
- Extract Color< 1 %
- Shape Appender< 1 %
- Interactive Table (legacy)< 1 %
- DB Query Reader< 1 %
- One Row to Many< 1 %
- Quasirandom Sequence Generator (Apache)< 1 %
- Visual 2D Data Generator< 1 %
- K Nearest Neighbor (Distance Function)< 1 %
- Pie/Donut Chart (JavaScript)< 1 %
- Prediction Fusion< 1 %
- Explorer Browser< 1 %
- Math Formula (Variable)< 1 %
- LIBSVMPredictor< 1 %
- SAS7BDAT Reader< 1 %
- Spark Line Appender< 1 %
- Chi-Square Keyword Extractor< 1 %
- Keygraph Keyword Extractor< 1 %
- NGram Creator< 1 %
- Kuhlen Stemmer< 1 %
- Snowball Stemmer< 1 %
- Stanford Lemmatizer< 1 %
Meta Info Extractor< 1 %- Sentence Extractor< 1 %
- Strings to Document< 1 %
- String to Term< 1 %
- Value Selection Configuration< 1 %
- Double Input (legacy)< 1 %
- File Chooser (legacy)< 1 %
- Integer Input (legacy)< 1 %
- Column Selection (legacy)< 1 %
- ROC Curve (JavaScript)< 1 %
- Tile View (JavaScript)< 1 %
- JSON Row Combiner< 1 %
- Container Output (Table)< 1 %
- String to JSON< 1 %
- Container Input (JSON)< 1 %
- JSON Path< 1 %
- Image Properties< 1 %
- Shapley Values Loop Start< 1 %
- Partition Table< 1 %
Python Predictor< 1 %- Python Source (legacy)< 1 %
- R Predictor< 1 %
- Create Test Blobs< 1 %
- UNIX Timestamp to Date&Time< 1 %
- Moving Aggregator< 1 %
- Discretise< 1 %
- RDKit Substructure Counter< 1 %
Column Distance< 1 %Ranking Services< 1 %- Table Column to Variable< 1 %
- Loop End< 1 %
- MDS< 1 %
- Gradient Boosted Trees to PMML< 1 %
- Column Name Extractor< 1 %
- Rank Correlation< 1 %
- CASE Switch End< 1 %
- PMML Transformation Apply< 1 %
- DB Numeric-Binner< 1 %
- H2O to Table< 1 %
- Word Vector Apply (legacy)< 1 %
- IDF< 1 %
- Bag Of Words Creator< 1 %
- Term Vector< 1 %
- Column Filter Configuration< 1 %
- Multiple Selection Widget< 1 %
- LIME Loop Start< 1 %
- RDKit Fingerprint< 1 %
Views
- Decision Tree View
- The decision tree as given in the model port along with the classified data. The tree can be expanded and collapsed with the plus/minus signs.
- Decision Tree View (simple)
- The decision tree as given in the model port along with the classified data.
Workflows
Credit Scoring Model(diksha kumari)KNIME Hub- !Modern UI_ABC-XYX-RFM AutoML SuperstoreKNIME Hub
- (test) credit score modelKNIME Hub
- [Latest] Consolidated 3 Mar 1210KNIME Hub
- 0_install_AI_extensionsKNIME Hub
- Show all 1778 workflows
Links
- KNIME E-Learning Course: Decision Treewww.knime.com/knime-introductory-course/chapter6/section3/decision-tree
- Help!- Churn for Bank Customers Analyzingby gonhaddock on 2022-05-18forum.knime.com/p/157353
Developers
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