**22**
results

- Go to itemThis loop closes a parameter optimization loop. It collects the objective function value from a flow variable and transfer the in…0
- 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 itemThis loop starts a parameter optimization loop. It takes a table as input. In the dialog you can map the parameters of the table …0
- Go to itemThis node applies the Apache Spark Logistic Regression algorithm. It outputs the the learned model for later application. Please …0
- Go to itemThis node takes two input tables: the first table contains all objects/rows from which subsets are selected. The second input tab…0
- Go to itemThis node finds (near)optimal fixed-sized subsets of rows based one one or more criteria. It uses the NSGA-II algorithm to find a…0
- Go to itemThis node uses the Score Erosion algorithm in order to select subsets of items/rows that have a high overall score, and are as di…0
- Go to itemThis node trains a support vector machine on the input data. It supports a number of different kernels (HyperTangent, Polynomial …0
- Go to itemThe rows from the input table are filtered according to one selected solution (which is a set of row keys) from a previous optimi…0
- Go to itemThis node uses the spark.ml linear regression implementation to train a linear regression model in Spark, supporting different re…0
- Go to itemPerforms a multinomial logistic regression. Select in the dialog a target column (combo box on top), i.e. the response. The solve…0
- Go to itemThis node is the start of the feature selection loop. The feature selection loop allows you to select, from all the features in t…0
- Go to itemThis node uses the spark.ml logistic regression implementation to train a logistic regression model in Spark, supporting differen…0
- Go to itemThis node is the start of the feature selection loop. The feature selection loop allows you to select, from all the features in t…0
- Go to itemThe node provides different algorithms to searches for frequent items in a list of item sets. The integrated algorithms are: Apri…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 itemLIBSVM v2.89 is an integrated software for support vector classification. For a more detailed description - especially of the par…0
- Go to itemPerforms a multinomial logistic regression. Select in the dialog a target column (combo box on top), i.e. the response. The two l…0
- Go to itemPerforms a multinomial logistic regression. Select in the dialog a target column (combo box on top), i.e. the response. The two l…0
- Go to itemPerforms a multinomial logistic regression. Select in the dialog a target column (combo box on top), i.e. the response. The two l…0