Trains a Probabilistic Neural Network (PNN) based on the DDA
(Dynamic Decay Adjustment) method on labeled data using
Constructive Training of Probabilistic Neural Networks as the
underlying algorithm.
This algorithm generates rules based on numeric data. Each rule is
defined as high-dimensional Gaussian function that is adjusted by
two thresholds, theta minus and theta plus, to avoid conflicts with
rules of different classes. Each Gaussian function is defined by
a center vector (from the first covered instance) and a standard
deviation which is adjusted during training to cover only
non-conflicting instances. 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 rules after execution along with a number of of rule
measurements. The model output port contains the PNN model,
which can be used for prediction in the PNN Predictor node.
Options
Popular Successors
- PNN Predictor55 %
CSV Writer2 %- Decision Tree Learner2 %
- Decision Tree Predictor2 %
- MultiLayerPerceptron Predictor2 %
Excel Writer (XLS)2 %- Interactive Table (legacy)1 %
- Scorer1 %
- Model to Cell1 %
- Line Plot (JavaScript)1 %
- CSV Writer< 1 %
- PNN Learner (DDA)< 1 %
- Model Writer< 1 %
- X-Aggregator< 1 %
- RProp MLP Learner< 1 %
- Numeric Scorer< 1 %
- Boosting Learner Loop End< 1 %
- Scorer (JavaScript)< 1 %
- Fuzzy Rule Predictor< 1 %
- SVM Predictor< 1 %
- ROC Curve (JavaScript)< 1 %
Naive Bayes Learner< 1 %- Naive Bayes Learner< 1 %
Naive Bayes Predictor< 1 %- Fuzzy Rule Learner< 1 %
- Gradient Boosted Trees Learner< 1 %
- Number to String< 1 %
- Lag Column< 1 %
- Partitioning< 1 %
- Scatter Plot (legacy)< 1 %
- Color Manager< 1 %
- Rule Viewer (local) (Legacy)< 1 %
- Table View (JavaScript)< 1 %
K Nearest Neighbor< 1 %PCA< 1 %Numeric Scorer< 1 %- SVM Learner< 1 %
Concatenate (Optional in)< 1 %Joiner< 1 %- Ruleset Predictor< 1 %
- Lift Chart (legacy)< 1 %
- Line Plot (legacy)< 1 %
- ROC Curve (legacy)< 1 %
- Model Loop End< 1 %
- PMML Ensemble Predictor< 1 %
- Cell to PMML< 1 %
- Breakpoint< 1 %
Database Update< 1 %Database Writer< 1 %Database Looping< 1 %Model Writer< 1 %Table Writer< 1 %- Java Edit Variable< 1 %
- Java Snippet< 1 %
Loop End< 1 %- Cluster Assigner< 1 %
- Silhouette Coefficient< 1 %
- k-Means< 1 %
- Decision Tree to Image< 1 %
- K Nearest Neighbor< 1 %
- Linear Regression Learner< 1 %
- Regression Predictor< 1 %
Scorer< 1 %- Association Rule Learner< 1 %
- PCA< 1 %
Random Forest Learner< 1 %- Gradient Boosted Trees Predictor (Regression)< 1 %
- Random Forest Learner< 1 %
- Random Forest Learner (Regression)< 1 %
- Simple Regression Tree Learner< 1 %
- PMML Simple Regression Tree Predictor< 1 %
- Simple Regression Tree Predictor< 1 %
- Binner (Dictionary)< 1 %
Column Appender< 1 %- Constant Value Column< 1 %
Linear Correlation< 1 %- Linear Correlation< 1 %
- Domain Calculator< 1 %
- Column Filter< 1 %
- GroupBy< 1 %
- Subset Matcher< 1 %
Column Rename< 1 %Rank Correlation< 1 %- Data Explorer< 1 %
- Numeric Outliers< 1 %
- Statistics< 1 %
CASE Switch Model (End)< 1 %- Extract Table Dimension< 1 %
- Conditional Box Plot (legacy)< 1 %
- Crosstab< 1 %
- HiLite Table (legacy)< 1 %
- Histogram (legacy)< 1 %
- Interactive Histogram (legacy)< 1 %
- Parallel Coordinates (legacy)< 1 %
- Scatter Matrix (legacy)< 1 %
- PMML Transformation Apply< 1 %
- Matrix Distance< 1 %
- Similarity Search< 1 %
- Stacked Area Chart (JavaScript)< 1 %
- Model Loop Start< 1 %
- PMML Ensemble Loop End< 1 %
PMML Predictor< 1 %- Cell to Model< 1 %
Excel Writer (XLS)< 1 %- Excel Writer< 1 %
- Java Snippet Row Filter< 1 %
- Spark Line Appender< 1 %
- StanfordNLP NE Learner< 1 %
- Term Vector< 1 %
- Scatter Plot (JavaScript)< 1 %
- Hierarchy Extractor< 1 %
- Network Viewer< 1 %
- Data to Report (BIRT)< 1 %
Views
- Learner Statistics
- Displays a summary of the learning process.
Workflows
4. CASE SwitchKNIME Hub- 4. CASE SwitchKNIME Hub
- 4. CASE SwitchKNIME Hub
- 4. CASE SwitchKNIME Hub
- 4. CASE SwitchKNIME Hub
- Show all 40 workflows
Links
- No links available
Developers
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