The distributions of each parameter will be searched for outliers according to a method of choice and rows containing outliers will be removed.
Options
Popular Successors
CSV Writer7 %Linear Correlation6 %Number To String4 %Joiner3 %- Histogram (legacy)2 %
Cell Splitter2 %Loop End2 %- Column Filter2 %
Column Rename2 %- Java Snippet2 %
- Partitioning2 %
- Interactive Table (legacy)1 %
- Row Splitter1 %
- Normalize Plates (Z-Score)1 %
- 2D/3D Scatterplot1 %
- Value Counter1 %
- Interactive Histogram (legacy)1 %
- Missing Value1 %
- Line Plot (legacy)1 %
String To Number1 %- Correlation Filter1 %
- Normalizer1 %
- Scatter Matrix (legacy)1 %
Excel Writer (XLS)1 %- Regression Predictor1 %
- Equal Size Sampling< 1 %
Rank Correlation< 1 %- Hierarchical Clustering< 1 %
PCA< 1 %Concatenate (Optional in)< 1 %- One to Many< 1 %
- Sorter< 1 %
- Numeric Outliers< 1 %
- k-Means< 1 %
- Constant Value Column< 1 %
- Row Filter< 1 %
- GroupBy< 1 %
- String Manipulation< 1 %
- One-way ANOVA< 1 %
- Statistics< 1 %
- Conditional Box Plot (JavaScript)< 1 %
- Math Formula< 1 %
- Line Chart (JFreeChart)< 1 %
Scorer< 1 %- Linear Correlation< 1 %
- Plate Heatmap Viewer< 1 %
- X-Partitioner< 1 %
Naive Bayes Learner< 1 %- Hierarchical Clustering (DistMatrix)< 1 %
- Decision Tree Learner< 1 %
- Round Double< 1 %
- Rule-based Row Filter< 1 %
- End IF< 1 %
- Extract Table Dimension< 1 %
- Box Plot (legacy)< 1 %
- Color Manager< 1 %
- Scatter Plot (JFreeChart)< 1 %
XLS Writer< 1 %- Scatter Plot (JavaScript)< 1 %
- R Snippet< 1 %
- R View (Table)< 1 %
- Z-Primes (PC x NC)< 1 %
- SVM Predictor< 1 %
Random Forest Learner< 1 %- Concatenate< 1 %
- Scatter Plot (legacy)< 1 %
- Similarity Search< 1 %
Document vector< 1 %- Column Filter (legacy)< 1 %
Table Writer< 1 %- Group Loop Start< 1 %
- Random Forest Learner< 1 %
- Numeric Binner< 1 %
- Outlier Removal< 1 %
- R Plot< 1 %
- ARIMA Learner< 1 %
- Fuzzy Rule Predictor< 1 %
- RProp MLP Learner< 1 %
- Linear Regression Learner< 1 %
- Polynomial Regression Learner< 1 %
Cell Replacer< 1 %- Domain Calculator< 1 %
- Denormalizer< 1 %
- Table Transposer< 1 %
- String to Date&Time< 1 %
- Gradient Boosted Trees Learner (Regression)< 1 %
- Low Variance Filter< 1 %
- ARIMA Predictor< 1 %
- Fuzzy c-Means< 1 %
Regression Predictor< 1 %- SMOTE< 1 %
- SVM Learner< 1 %
Tree Ensemble Learner< 1 %- HiLite Row Splitter< 1 %
- Pivot< 1 %
String To Number (PMML)< 1 %- String Replacer< 1 %
- Conditional Box Plot (legacy)< 1 %
- Numeric Distances< 1 %
- GroupBy Bar Chart (JFreeChart)< 1 %
- OSM Map View< 1 %
- Moving Average< 1 %
- RDKit Interactive Table< 1 %
CV< 1 %Regression Predictor< 1 %Tree Ensemble Learner (Regression)< 1 %- Number to String< 1 %
- Cross Joiner< 1 %
- Rule-based Row Splitter< 1 %
- Table View (JavaScript)< 1 %
- CSV Writer< 1 %
- Duplicate Row Filter< 1 %
- Constant Value Column Filter< 1 %
- Group Mutual Information< 1 %
- Matlab Plot< 1 %
- ARIMA Visualization< 1 %
Variable to Table Column< 1 %Database Writer< 1 %Loop End (2 ports)< 1 %Generic Loop Start< 1 %k-Means< 1 %- Decision Tree Predictor< 1 %
PCA Compute< 1 %- Auto-Binner< 1 %
- Column Combiner< 1 %
- Category to Number< 1 %
Column Appender< 1 %- Reference Column Filter< 1 %
- Missing Value Column Filter< 1 %
- Nominal Value Row Filter< 1 %
- Reference Row Filter< 1 %
Normalizer< 1 %- Normalizer (PMML)< 1 %
- Row Sampling< 1 %
- Rule Engine< 1 %
- Independent groups t-test< 1 %
Color Appender< 1 %- Histogram Chart (JFreeChart)< 1 %
- Weka Predictor (3.7)< 1 %
- ROC Curve (JavaScript)< 1 %
- String to JSON< 1 %
- Image Viewer< 1 %
- Python View (legacy)< 1 %
- String to Date/Time (legacy)< 1 %
Map Viewer< 1 %- Time Domain Features (TDF)< 1 %
- Create Interval< 1 %
- Number Formatter< 1 %
- BinningAnalysis< 1 %
- Normalize Plates (NPI)< 1 %
- Normalize Plates (POC)< 1 %
Backward Feature Elimination Start (1:1)< 1 %- Naive Bayes Learner< 1 %
Naive Bayes Predictor< 1 %- Hierarchical Cluster View< 1 %
- DBSCAN< 1 %
PCA Apply< 1 %- Logistic Regression Predictor< 1 %
SVM Learner< 1 %Gradient Boosted Trees Learner< 1 %Gradient Boosted Trees Predictor< 1 %Gradient Boosted Trees Predictor< 1 %- Gradient Boosted Trees Predictor (Regression)< 1 %
- Tree Ensemble Learner< 1 %
- Tree Ensemble Learner (Regression)< 1 %
- Random Forest Learner (Regression)< 1 %
- Simple Regression Tree Learner< 1 %
- Column Resorter< 1 %
- One to Many (PMML)< 1 %
- RowID< 1 %
- Numeric Row Splitter< 1 %
- Rank Correlation< 1 %
- Data Explorer< 1 %
- Shapiro-Wilk Test< 1 %
- Kolmogorov-Smirnov Test< 1 %
- Paired t-test< 1 %
- Extract Table Spec< 1 %
- Crosstab< 1 %
- HiLite Table (legacy)< 1 %
- Box Plot (JavaScript)< 1 %
- Histogram (JavaScript)< 1 %
- Table to H2O< 1 %
- Math Formula (Multi Column)< 1 %
- Pie Chart (JFreeChart)< 1 %
- LIBSVMLearner< 1 %
- Score Erosion< 1 %
Python Script (1⇒1)< 1 %Extract Date&Time Fields< 1 %- Moving Aggregator< 1 %
XGBoost Tree Ensemble Learner (Regression)< 1 %- Result< 1 %
- Information Gain Calculator< 1 %
- Multivariate Z-Primes< 1 %
- CV< 1 %
- Lag Column< 1 %
- Column Splitter< 1 %
- Table Difference Finder< 1 %
- Violin Plot (Plotly)< 1 %
- Excel Writer< 1 %
- Line Plot (JavaScript)< 1 %
- Python Script (legacy)< 1 %
- 3D Coordinates< 1 %
Views
- This node has no views
Workflows
03_Normalization_of_screening_dataKNIME Hub- Customer SegmentationKNIME Hub
- House_pricing1KNIME Hub
- House_pricing2KNIME Hub
- Web_profiling_recomendation1KNIME Hub
- Show all 6 workflows
Links
- No links available
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.