221 results
- Go to itemThis workflow showcases 1 example where the Process Mining View component is adopted on sales data. It is recommended to interact…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 itemThis node induces a classification decision tree in main memory. The target attribute must be nominal. The other attributes used …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 loop starts a parameter optimization loop. In the dialog you can enter several parameters with an interval and a step size. …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 workflow showcases 1 example where the Process Mining View component is adopted on e-commerce data. It is recommended to int…0
- Go to itemThis workflow showcases 7 different examples where the Process Mining View component is adopted. This verified component works on…0
- Go to itemThis workflow showcases 1 example where the Process Mining View component is adopted on healthcare data. It is recommended to int…0
- Go to itemMeta collection about KNIME and Text analytics and Text mining This is a documentation about KNIME and Text processing https://ww…0
- Go to itemThis workflow showcases 1 example where the Process Mining View component is adopted on customer service data. It is recommended …0
- Go to itemThe association rule learner* searches for frequent itemsets meeting the user-defined minimum support criterion and, optionally, …0
- Go to itemThis rule learner* uses the Apriori (Agrawal et al. 1993) algorithm implemented by Christian Borgelt. The following description h…0
- Go to itemThis is the end node of a backward feature elimination loop. It compares the target column with the prediction column set in the …0
- Go to itemThis node takes a model built with a feature elimination loop and lets you choose the column you want to include in the output ta…0
- Go to itemThis is the start node of a backward feature elimination loop. The first iteration of the loop is executed with all input columns…0
- Go to itemThis is the start node of a backward feature elimination loop. The first iteration of the loop is executed with all input columns…0