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- Go to itemThis workflow is an example of how to build a basic prediction / classification model using a decision tree. Dataset describes wi…3
- Go to itemThis workflow is an example of how to build a basic prediction / classification model using logistic regression.2
- Go to itemThis node induces a classification decision tree in main memory. The target attribute must be nominal. The other attributes used …2
- Go to itemCalculates for each pair of selected columns a correlation coefficient, i.e. a measure of the correlation of the two variables. W…2
- Go to itemTraining a decision tree and training a random forest of decision trees. Adult.csv dataset describes US census information. Outpu…1
- Go to itemThis workflow solves a binary classification problem on the adult dataset using more advanced algorithms: - Random Forest - Gradi…1
- Go to itemThis workflow creates a model selction on the webportal, where data analysts can choose a training and a test set between the dat…1
- Go to itemThis node uses the model as generated by a Correlation node to determine which columns are redundant (i.e. correlated) and filter…1
- Go to itemComputes the Cronbach Alpha for all numerical columns based on their variance. Cronbach's Alpha compares the variance of the indi…1
- Go to itemCalculates distance values for all pairs of rows of the input table. The result is appended to the input table as a single column…1
- Go to itemThis rule learner* learns a Fuzzy Rule Model on labeled numeric data using Mixed Fuzzy Rule Formation as the underlying training …1
- Go to itemThis view takes a hierarchical cluster tree and the same input table, that has been used for the creating the clustering and visu…1
- Go to itemFilters out double-compatible columns, whose variance is below a user defined threshold. Columns with low variance are likely to …1
- Go to itemBased on a trained MultiLayerPerceptron-model given at the model inport of this node, the expected output values are computed. If…1
- Go to itemThis node detects and treats the outliers for each of the selected columns individually by means of interquartile range (IQR) . T…1
- Go to itemThis loop starts a parameter optimization loop. In the dialog you can enter several parameters with an interval and a step size. …1
- Go to itemCalculates for each pair of selected columns a correlation coefficient, i.e. a measure of the correlation of the two variables. A…1
- Go to itemCompares two columns by their attribute value pairs and shows the confusion matrix, i.e. how many rows of which attribute and the…1
- Go to itemThis node takes each row in the query table (Port 0) and searches the reference table (Port 1) for a number of rows matching the …1