This rule learner* learns a Fuzzy Rule Model on labeled numeric data using
Mixed Fuzzy Rule Formation as the underlying training algorithm
(also known as RecBF-DDA algorithm),
see
Influence of fuzzy norms and other heuristics on
"Mixed Fuzzy Rule Formation" for an extension of the algorithm.
This algorithm generates rules based on numeric data, which are
fuzzy intervals in higher dimensional spaces. These
hyper-rectangles are defined by trapezoid fuzzy membership functions for
each dimension. The selected numeric columns of the input data are used
as input data for training and additional columns are used as
classification target, either one column holding the class information
or a number of numeric columns with class degrees between 0 and 1 can
be selected. The data output contains the fuzzy rules after execution.
Each rule consists of one fuzzy interval for each dimension plus
the target classification columns along with a number of rule
measurements. The model output port contains the fuzzy
rule model, which can be used for prediction in the Fuzzy Rule Predictor
node.
(*) RULE LEARNER is a registered trademark of Minitab, LLC and is used with Minitab’s permission.
Options
Popular Predecessors
Excel Reader (XLS)8 %String To Number3 %- Joiner3 %
- Excel Reader2 %
Scorer2 %Row Splitter (deprecated)2 %- Rule Engine2 %
- Math Formula2 %
- Math Formula (Multi Column)2 %
Number To String2 %- GroupBy2 %
XLS Reader2 %Excel Reader (XLS)2 %- ARFF Reader1 %
- SMOTE1 %
Joiner1 %- Partitioning1 %
- String Manipulation1 %
- Java Snippet (simple)1 %
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K Nearest Neighbor1 %- Create Bit Vector1 %
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- Fuzzy Rule Learner1 %
- Number to String1 %
- String to Number1 %
- Similarity Search1 %
- Pivot1 %
- Strings to Binary Objects< 1 %
- Fuzzy Rule Predictor< 1 %
- Equal Size Sampling< 1 %
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Row Filter (deprecated)< 1 %- Normalizer< 1 %
- Missing Value< 1 %
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Linear Correlation< 1 %- Row Sampling< 1 %
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- Rule Engine (Dictionary)< 1 %
Excel Reader (XLS)< 1 %- Statistics< 1 %
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Naive Bayes Learner< 1 %- PNN Learner (DDA)< 1 %
- One to Many< 1 %
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Table Row To Variable Loop Start< 1 %CSV Reader< 1 %Database Reader< 1 %File Reader< 1 %- Table Creator< 1 %
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- Association Rule Learner< 1 %
Random Forest Predictor< 1 %Cell Splitter< 1 %- Category to Number< 1 %
Column Appender< 1 %- Column Renamer (Dictionary)< 1 %
- Constant Value Column< 1 %
- Reference Row Splitter< 1 %
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Read XLS Sheet Names< 1 %- IDF< 1 %
Bag of Words Creator< 1 %- Weka Predictor (3.7)< 1 %
Python Script (1⇒2)< 1 %- Date&Time to legacy Date&Time< 1 %
- String to Date/Time (legacy)< 1 %
- Breakpoint< 1 %
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Recursive Loop Start< 1 %- PNN Predictor< 1 %
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Concatenate (Optional in)< 1 %- Cell Splitter< 1 %
- Column Auto Type Cast< 1 %
- Domain Calculator< 1 %
- Double to Integer< 1 %
- Constant Value Column Filter< 1 %
- Interactive HiLite Collector< 1 %
- Subset Matcher< 1 %
- Missing Value (Apply)< 1 %
- Normalizer (PMML)< 1 %
String To Number (PMML)< 1 %- Number Rounder< 1 %
- RowID< 1 %
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Merge Variables< 1 %- Lift Chart (legacy)< 1 %
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MongoDB Reader< 1 %- Date&Time Difference< 1 %
- Date&Time-based Row Filter< 1 %
- Modify Date< 1 %
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- Column Combiner< 1 %
- String to Number (PMML)< 1 %
- Shuffle< 1 %
- String Manipulation (Multi Column)< 1 %
String Replace (Dictionary)< 1 %- Table Transposer< 1 %
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Views
- Learner Statistics
- Displays a summary of the learning process.
Workflows
2_bisKNIME Forum- Basketball Hubversion 2.2KNIME Hub
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