**361**
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- 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 itemPer verificare se i valori elevati di accuratezza dell'algoritmo Logistic regression non siano dovuti ad overfitting, in questa v…0
- Go to itemThis classifier generates a two-class kernel logistic regression model The model is fit by minimizing the negative log-likelihood…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 itemImplements John Platt's sequential minimal optimization algorithm for training a support vector classifier. This implementation g…0
- Go to itemImplements John Platt's sequential minimal optimization algorithm for training a support vector classifier. This implementation g…0
- Go to itemClass for building and using a multinomial logistic regression model with a ridge estimator. There are some modifications, howeve…0
- Go to itemClass for building and using a multinomial logistic regression model with a ridge estimator. There are some modifications, howeve…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 itemClass for generating a PART decision list Uses separate-and-conquer.Builds a partial C4.5 decision tree in each iteration and mak…0
- Go to itemClass for generating a PART decision list. Uses separate-and-conquer. Builds a partial C4.5 decision tree in each iteration and m…0
- Go to itemSMOreg implements the support vector machine for regression. The parameters can be learned using various algorithms. The algorith…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 class implements a propositional rule learner*, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was …0