Outlier Removal

The distributions of each parameter will be searched for outliers according to a method of choice and rows containing outliers will be removed.

Options

Method
The method to determine the lower and upper bounds of the data (outlier limits). Mean +- SD: This assumes a normal distribution. outliers are defined to be greater than "Mean + Factor*SD" or smaller than "Mean - Factor*SD". Factor is 3 per default. Boxplot: outliers are defined to be greater than "Q85+Factor*IQR" or smaller than "Q25 - Factor*IQR", where Q are the quantiles and IQR is the inter quantile range. Be careful the default 3 goes with the default method (Mean +- SD). A standard value for this method would be 1.5.
Factor
The factor multiplies the value describing the spread of the distribution.
Subsets
Select the columns by which the measurements should be grouped (example: plates, batches, runs...)
Constraints
The first column filter allows to select multiple columns to define groups. Rows that share the same values for all constraint columns belong to one and the same group.
Parameter
The second column filter is to select the paramters where the values have to be ckecked for outliers.
All Parameter
Per default unchecked. In this case an row is removed if it has an outlier value for at least one parameter. If you tick this checkbox, the row is only removed if all the values for all parameter are outliers.

Input Ports

Icon
data for outlier analysis

Output Ports

Icon
table with outlier rows removed.
Icon
No description for this port available.

Popular Predecessors

Popular Successors

  • CSV Writer7 %
  • Linear Correlation6 %
  • Number To String4 %
  • Joiner3 %
  • Histogram3 %
  • Cell Splitter2 %
  • Loop End2 %
  • Column Rename2 %
  • Java Snippet2 %
  • Interactive Table (local)2 %
  • Row Splitter1 %
  • Normalize Plates (Z-Score)1 %
  • 2D/3D Scatterplot1 %
  • Value Counter1 %
  • Histogram (interactive)1 %
  • Line Plot1 %
  • Regression Predictor1 %
  • String To Number1 %
  • Correlation Filter1 %
  • Scatter Matrix1 %
  • Excel Writer (XLS)1 %
  • 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 %
  • Scorer< 1 %
  • Linear Correlation< 1 %
  • Partitioning< 1 %
  • String Manipulation< 1 %
  • One-way ANOVA< 1 %
  • Statistics< 1 %
  • Box Plot< 1 %
  • Conditional Box Plot (JavaScript)< 1 %
  • Line Chart (JFreeChart)< 1 %
  • Plate Heatmap Viewer< 1 %
  • X-Partitioner< 1 %
  • Naive Bayes Learner< 1 %
  • Hierarchical Clustering (DistMatrix)< 1 %
  • k-Means< 1 %
  • Decision Tree Learner< 1 %
  • Concatenate< 1 %
  • Constant Value Column< 1 %
  • Column Filter< 1 %
  • Row Filter< 1 %
  • GroupBy< 1 %
  • Normalizer< 1 %
  • Missing Value< 1 %
  • Round Double< 1 %
  • Rule-based Row Filter< 1 %
  • End IF< 1 %
  • Extract Table Dimension< 1 %
  • Box Plot (local)< 1 %
  • Color Manager< 1 %
  • Conditional Box Plot< 1 %
  • Math Formula< 1 %
  • Scatter Plot (JFreeChart)< 1 %
  • XLS Writer< 1 %
  • Excel Writer< 1 %
  • Scatter Plot< 1 %
  • R Snippet< 1 %
  • R View (Table)< 1 %
  • Z-Primes (PC x NC)< 1 %
  • Table Writer< 1 %
  • Group Loop Start< 1 %
  • SVM Predictor< 1 %
  • Random Forest Learner< 1 %
  • Random Forest Learner< 1 %
  • Numeric Binner< 1 %
  • Scatter Plot (local)< 1 %
  • Similarity Search< 1 %
  • Document vector< 1 %
  • Column Filter< 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 %
  • Gradient Boosted Trees Learner (Regression)< 1 %
  • Cell Replacer< 1 %
  • Domain Calculator< 1 %
  • Low Variance Filter< 1 %
  • Denormalizer< 1 %
  • Transpose< 1 %
  • JavaScript Bar Chart< 1 %
  • String to Date&Time< 1 %
  • CV< 1 %
  • ARIMA Predictor< 1 %
  • CSV Writer< 1 %
  • Fuzzy c-Means< 1 %
  • Regression Predictor (deprecated)< 1 %
  • Regression Predictor< 1 %
  • SMOTE< 1 %
  • SVM Learner< 1 %
  • Tree Ensemble Learner (Regression)< 1 %
  • Tree Ensemble Learner< 1 %
  • Number To String< 1 %
  • Cross Joiner< 1 %
  • Duplicate Row Filter< 1 %
  • Constant Value Column Filter< 1 %
  • HiLite Row Splitter< 1 %
  • Pivoting< 1 %
  • String To Number (PMML)< 1 %
  • String Replacer< 1 %
  • Rule-based Row Splitter< 1 %
  • Conditional Box Plot (local)< 1 %
  • Numeric Distances< 1 %
  • GroupBy Bar Chart (JFreeChart)< 1 %
  • OSM Map View< 1 %
  • Table View (JavaScript)< 1 %
  • Moving Average< 1 %
  • RDKit Interactive Table< 1 %
  • Time Domain Features (TDF)< 1 %
  • RapidMiner Viewer< 1 %
  • Create Interval< 1 %
  • Number Formatter< 1 %
  • BinningAnalysis< 1 %
  • Normalize Plates (NPI)< 1 %
  • Normalize Plates (POC)< 1 %
  • Group Mutual Information< 1 %
  • Multivariate Z-Primes< 1 %
  • CV< 1 %
  • Matlab Plot< 1 %
  • ARIMA Visualization< 1 %
  • Variable to Table Column< 1 %
  • Database Writer (legacy)< 1 %
  • Backward Feature Elimination Start (1:1)< 1 %
  • Loop End (2 ports)< 1 %
  • Generic Loop Start< 1 %
  • Naive Bayes Learner< 1 %
  • Naive Bayes Predictor< 1 %
  • Hierarchical Cluster View< 1 %
  • k-Means< 1 %
  • DBSCAN< 1 %
  • Decision Tree Predictor< 1 %
  • PCA Apply< 1 %
  • PCA Compute< 1 %
  • Logistic Regression Predictor< 1 %
  • SVM Learner (deprecated)< 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 %
  • Auto-Binner< 1 %
  • Column Combiner< 1 %
  • Category To Number< 1 %
  • Column Appender< 1 %
  • Lag Column< 1 %
  • Column Resorter< 1 %
  • Reference Column Filter< 1 %
  • Missing Value Column Filter< 1 %
  • Nominal Value Row Filter< 1 %
  • Reference Row Filter< 1 %
  • Normalizer< 1 %
  • One to Many (PMML)< 1 %
  • Normalizer (PMML)< 1 %
  • RowID< 1 %
  • Numeric Row Splitter< 1 %
  • Row Sampling< 1 %
  • Column Splitter< 1 %
  • Table Difference Finder< 1 %
  • Rule Engine< 1 %
  • Rank Correlation< 1 %
  • Data Explorer< 1 %
  • Shapiro-Wilk Normality Test< 1 %
  • Kolmogorov-Smirnov Test< 1 %
  • Paired t-test< 1 %
  • Independent groups t-test< 1 %
  • Extract Table Spec< 1 %
  • Crosstab< 1 %
  • HiLite Table< 1 %
  • Color Appender< 1 %
  • WrappedNode Output< 1 %
  • JavaScript Box Plot< 1 %
  • JavaScript Conditional Box Plot< 1 %
  • Box Plot (JavaScript)< 1 %
  • Histogram< 1 %
  • Histogram (JavaScript)< 1 %
  • Violin Plot (Plotly)< 1 %
  • Table to H2O< 1 %
  • Math Formula (Multi Column)< 1 %
  • Histogram Chart (JFreeChart)< 1 %
  • Pie Chart (JFreeChart)< 1 %
  • LIBSVMLearner< 1 %
  • Id3 (3.7)< 1 %
  • Weka Predictor (3.7)< 1 %
  • Line Plot< 1 %
  • ROC Curve (JavaScript)< 1 %
  • String to JSON< 1 %
  • Image Viewer< 1 %
  • Score Erosion< 1 %
  • Python Script (1⇒1)< 1 %
  • Python Script< 1 %
  • Python View< 1 %
  • Extract Date&Time Fields< 1 %
  • Moving Aggregation< 1 %
  • String to Date/Time (legacy)< 1 %
  • XGBoost Tree Ensemble Learner (Regression)< 1 %
  • Result< 1 %
  • 3D Coordinates< 1 %
  • Information Gain Calculator< 1 %
  • Map Viewer< 1 %

Views

This node has no views

Workflows

Links

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.