**2 150**
results

**2 150**
results

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###### Evaluating Classification Model Performance

This workflow trains a classification model using the Decision Tree algorithm and evaluates its accuracy by scoring metrics, ROC …knime > Examples > 04_Analytics > 10_Scoring > 01_Evaluating_Classification_Model_Performance4 - Go to itemIn this example we take a look at the KNIME Nodes for H2O Scoring. There are different H2O Scorer Nodes in KNIME for different Ma…knime > Examples > 04_Analytics > 15_H2O_Machine_Learning > 05_H2O_Scoring0
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###### Evaluating the Performance of a Regression Model

This workflow trains a linear regression model that predicts the amount of a credit. The performance of the linear regression mod…knime > Examples > 04_Analytics > 10_Scoring > 04_Evaluating_Regression_Model_Performance2 - Go to itemWorkflow
###### Weak Supervision on the Adult dataset

This workflow shows how to use the Weak Label Model Learner and Predictor nodes to aggregate sources of weak supervision such as …knime > Examples > 04_Analytics > 13_Meta_Learning > 05_Weak_Supervision_on_the_Adult_dataset0 - Go to itemCalculates various performance measures (detailed below) on the input table. This node also takes a column to bin the values on, …0
- Go to itemThis node is based on the alignment result from PNReplayer, and calculates the performance information on Petri net. Usually, Str…0
- Go to itemIntroduction to Machine Learning Algorithms course - Session 2 Exercise 4 - Train a logistic regression model - Apply the model t…knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_2 > 01_Exercises > 04_Logistic_Regression0
- Go to itemLogistic Regression: predict wine color. - Normalize numerical columns - Partition the dataset into train and test set - Train a …knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Regression > Logistic_Regression_Solution0
- Go to itemLogistic Regression: predict wine color. - Normalize numerical columns - Partition the dataset into train and test set - Train a …knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Regression > Logistic_Regression_Exercise0
- Go to itemIntroduction to Machine Learning Algorithms course - Session 1 Exercise 1 - Partition data into training and test set - Train a d…knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_1 > 01_Exercises > Decision_Tree0
- Go to itemIntroduction to Machine Learning Algorithms course - Session 2 Exercise 3 - Train a Random Forest model - Apply the model to the …knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_2 > 01_Exercises > 03_Random_Forest0
- Go to itemSolution to an exercise for training a model for numeric prediction. Train and apply a linear regression model. Evaluate the perf…knime > Education > Self-Paced Courses > L1-DS KNIME Analytics Platform for Data Scientists - Basics > Solutions > 08 Regression Model - Solution1
- Go to itemIntroduction to Machine Learning Algorithms course - Session 2 Solution to exercise 3 - Train a random forest model - Apply the m…knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_2 > 02_Solutions > 03_Random_Forest_solution0
- Go to itemLinear regression: predict house price. - Partition data into training and test set - Train a linear regression model - Apply the…knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Regression > Linear_Regression_Exercise0
- Go to itemRegression Tree: predict house price. - Partition data into training and test set - Train a regression tree model - Apply the tra…knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Decision_and_Regression_Trees > Regression_Tree_Solution0

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