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Exercise3

<p><strong>Chapter 4/Exercise 3</strong></p><p>This workflow is another exerciser for classification training a Naive Bayes Learner model using data of the <em>website1.txt</em> file.</p><p>First, it's calculating basic stats of the number of visitors ("no visitors"). Then, after some preprocessing, it's training a Naive Bayes model (<em>Naive Bayer Learner</em> node) to classify "weekend" vs. "no weekend" according to the number of visitors of a website. Lastly, it's evaluating the model by calculating a confusion matrix (<em>Scorer </em>node) and visualizing the area under the curve (AuC) (<em>ROC Curve</em> node).<br></p>

URL: KNIME Beginner's Luck (Book Homepage) https://www.knime.com/knimepress/beginners-luck

Workflow: Chapter 4/Exercise 3


This workflow is another exerciser for classification training a Naive Bayes Learner model using data of the website1.txt file.

First, it's calculating basic stats of the number of visitors ("no visitors"). Then, after some preprocessing, it's training a Naive Bayes model (Naive Bayer Learner node) to classify "weekend" vs. "no weekend" according to the number of visitors of a website. Lastly, it's evaluating the model by calculating a confusion matrix (Scorer node) and visualizing the area under the curve (AuC) (ROC Curve node).

Reading data

Transforming data

Training model

Applying trained model

Evaluating model

Basic statistics

website1.txt
CSV Reader
Target value:"binary_class"
Naive Bayes Learner
Area under the Curve
ROC Curve
Basic statistics of"no visitors"
Statistics View
Naive Bayes Predictor
Keep only"no visitors" and"binary_class"
Column Filter
Create "binary_class" columnindicated "weekend" or "not weekend"
Expression
Confusion matrixbinary_class vs. Prediction (binary_class)
Scorer

Nodes

Extensions

Links