Partitioning
Manipulator
The input table is split into two partitions (i.e. rowwise), e.g. train and test data. The two partitions are available at the two output ports. The following options are available in the dialog:
Input Ports
 Type: Data Table to partition.
Output Ports
 Type: Data First partition (as defined in dialog).
 Type: Data Second partition (remaining rows).

How to use the Tree Ensemble nodes
This workflow shows how the tree ensemble nodes can be used for regression and classification tasks. Note: If you want t…aajaradata > 03_Learning_a_Tree_Ensemble_Model 
Variable Importance
This workflow calculates how important each variable is for a correct classification.aajaradata > 04_Meassuring_Variable_Importance 
My_First_Project_Home
djibrinabarry > My_First_Project_Home 
Optimizing Classification Threshold Based on Profit
classification model model evaluation profit cost accuracy classification thresholdTrain a classification model using the Linear Regression algorithm. Evaluate the class prediction by overall accuracy an…shima0011 > 04_Analytics > 10_Scoring > 02_Optimizing_Classification_Threshold_Based_on_Profit 
Naive Bayes
A simple example using a Naive Bayes learner and predictor to classify some shuttle data. For more background informatio…shima0011 > 04_Analytics > 04_Classification_and_Predictive_Modelling > 03_Example_for_Learning_a_Naive_Bayes_Model 
Logistic Regression
classification machine learning prediction analytics KNIME logistic regression logit data scienceThis workflow is an example of how to build a basic prediction / classification model using logistic regression.shima0011 > 04_Analytics > 04_Classification_and_Predictive_Modelling > 06_Logistic_Regression 
How to use the Simple Regression Tree
This workflow illustrates how to use the Simple Regression Tree nodes to predict the value of a numerical target column.shima0011 > 04_Analytics > 05_Regressions > 01_Learning_a_Simple_Regression_Tree 
Semantic Segmentation with Deep Learning in KNIME
deep learning image processing image analysis computer vision unet neural network segmentation semantic segmentation encoder decoder pixel classificationThis workflow shows how the new KNIME Keras integration can be used to train and deploy a specialized deep neural networ…shima0011 > 04_Analytics > 14_Deep_Learning > 02_Keras > 06_Semantic_Segmentation 
Sentiment Analysis
deep learning keras text classification classification lstm embedding text analysis sequence analysis sentiment analysis sequence classification neural network text processingThis workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The u…shima0011 > 04_Analytics > 14_Deep_Learning > 02_Keras > 07_Sentiment_Analysis_with_Deep_Learning 
Training a Churn Predictor
This workflow is an example of how to build a basic PMML model for a churn prediction using a Decision Tree algorithm.dainq > Churn Prediction > Building a Churn Prediction Model