Classifies a set of test data based on the k Nearest Neighbor algorithm using the training data. The underlying algorithm uses a KD tree and should therefore exhibit reasonable performance. However, this type of classifier is still only suited for a few thousand to ten thousand or so training instances. All (and only) numeric columns and the Euclidean distance are used in this implementation. All other columns (of non-numeric type) in the test data are being forwarded as-is to the output.
Options
Popular Predecessors
- Partitioning18 %
- Normalizer (Apply)7 %
- Normalizer5 %
- X-Partitioner5 %
- Column Filter4 %
Scorer4 %- Excel Reader3 %
Excel Reader (XLS)2 %Number To String2 %Table Row to Variable2 %- ARFF Reader1 %
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String To Number< 1 %Table Row to Variable< 1 %- SMOTE< 1 %
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Counting Loop Start< 1 %- Missing Value< 1 %
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- PMML Transformation Apply< 1 %
- Hierarchical Clustering< 1 %
- String to Number< 1 %
Linear Correlation< 1 %- Number to String (PMML)< 1 %
- RowID< 1 %
- Rule-based Row Filter< 1 %
- Table Row to Variable Loop Start< 1 %
- Scatter Plot (Plotly)< 1 %
- Decision Tree Predictor< 1 %
- Rule Engine< 1 %
- Numeric Outliers< 1 %
Color Appender< 1 %- k-Medoids< 1 %
Excel Reader (XLS)< 1 %- Value Counter< 1 %
CSV Reader< 1 %File Reader< 1 %- Table Creator< 1 %
Row Splitter (deprecated)< 1 %- K Nearest Neighbor< 1 %
- Auto-Binner< 1 %
- One to Many< 1 %
- GroupBy< 1 %
String Replace (Dictionary)< 1 %- Similarity Search< 1 %
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- Scorer< 1 %
- Read Excel Sheet Names< 1 %
- Date&Time Difference< 1 %
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- Hierarchical Cluster Assigner (local)< 1 %
- Logistic Regression Learner< 1 %
- Logistic Regression Predictor< 1 %
- Random Forest Learner< 1 %
- Bootstrap Sampling< 1 %
Column Appender< 1 %- Column Resorter< 1 %
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- Missing Value Column Filter< 1 %
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- Normalizer (PMML)< 1 %
- Row Sampling< 1 %
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- Statistics< 1 %
- Distance Matrix Calculate< 1 %
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- Strings to Document< 1 %
- Table Column to Variable< 1 %
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- Table Reader< 1 %
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- Joiner< 1 %
- Loop End< 1 %
- Data Explorer< 1 %
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Joiner< 1 %- Pivot< 1 %
- Decision Tree to Ruleset< 1 %
Table Row To Variable Loop Start< 1 %Number To String (PMML)< 1 %- Shuffle< 1 %
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- Regression Predictor< 1 %
- SVM Predictor< 1 %
- Crosstab< 1 %
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Loop End< 1 %- PNN Predictor< 1 %
- Cluster Assigner< 1 %
PCA Apply< 1 %- Auto-Binner (Apply)< 1 %
- Linear Correlation< 1 %
- Correlation Filter< 1 %
- Table Validator< 1 %
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- Feature Calculator (BETA)< 1 %
- OpenBabel< 1 %
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Generic Loop Start< 1 %- MultiLayerPerceptron Predictor< 1 %
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- Double to Integer< 1 %
- Interactive HiLite Collector< 1 %
- Nominal Value Row Filter< 1 %
- Numeric Row Splitter< 1 %
- Column Expressions< 1 %
- Value Filter (legacy)< 1 %
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- Heatmap (JavaScript)< 1 %
- Table Row To Variable Run-for-time Loop Start< 1 %
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- Group Loop Start< 1 %
- Edit Numeric Domain< 1 %
- Rank< 1 %
- Shape Appender< 1 %
- Document Vector Hashing< 1 %
- Forge Build Machine Learning< 1 %
- Vector Length Normalization< 1 %
- Create Collection Column< 1 %
- Split Collection Column< 1 %
Table Column to Variable< 1 %Database Reader< 1 %PMML Writer< 1 %- Java Edit Variable< 1 %
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- Feature Selection Filter< 1 %
Loop End (2 ports)< 1 %- Fuzzy Rule Learner< 1 %
- PNN Learner (DDA)< 1 %
- Fuzzy c-Means< 1 %
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- MDS< 1 %
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PCA Compute< 1 %PCA< 1 %- Linear Regression Learner< 1 %
- Numeric Scorer< 1 %
- SVM Learner< 1 %
- Gradient Boosted Trees Predictor< 1 %
- Gradient Boosted Trees Predictor (Regression)< 1 %
- Random Forest Learner (Regression)< 1 %
- Numeric Binner< 1 %
- Expand Bit Vector< 1 %
- Column Auto Type Cast< 1 %
- Column Combiner< 1 %
- Number to Category (Apply)< 1 %
- Column Rename (Regex)< 1 %
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- Cross Joiner< 1 %
- Extract Missing Value Cause< 1 %
- Filter Apply< 1 %
- HiLite Row Splitter< 1 %
- Nominal Value Row Splitter< 1 %
- Reference Row Filter< 1 %
- DB Query Reader< 1 %
- Random Label Assigner< 1 %
- Random Boolean Assigner< 1 %
- 3D Scatter Plot (Plotly)< 1 %
- Boosting Predictor Loop Start< 1 %
- Math Formula (Variable)< 1 %
- Term Co-Occurrence Counter< 1 %
- Document Vector< 1 %
- Term Neighborhood Extractor< 1 %
- Weka Predictor (3.7)< 1 %
- Boolean Input (legacy)< 1 %
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JSON Reader< 1 %- Labeling to Image< 1 %
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- Variable to Table Column< 1 %
Table Reader< 1 %Table Row To Variable Loop Start< 1 %- Entropy Scorer< 1 %
- PCA Apply< 1 %
- Column Appender< 1 %
- Edit Nominal Domain< 1 %
- Duplicate Row Filter< 1 %
- Row Filter (Labs)< 1 %
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- Top k Row Filter< 1 %
- Rank Correlation< 1 %
- Numeric Outliers (Apply)< 1 %
- Data Generator< 1 %
- Random Number Assigner< 1 %
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- RDKit Fingerprint< 1 %
- BERT Classification Learner< 1 %
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