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INE 418 Mini Project 2_​Group 3_​KNIME Workflow.knwf (1)

GroupBy
Visualizing the data
Statistics
Numeric Binner
Bar Chart
Generating the ROC Curve
ROC Curve
Evaluating the performanceof the model
Scorer (JavaScript)
Generating the ROC Curve
ROC Curve
Numeric Binner
Bar Chart
Training the Random Forestclassification model
Random Forest Learner
Predicting using the RandomForest classification model
Random Forest Predictor
Training the SVMclassification model
SVM Learner
Checking the presence or proportion of "At Risk"and "Not at Risk" classes in the training dataset
Statistics
Predicting using the SVMclassification model
SVM Predictor
Checking the presence or proportion of "At Risk"and "Not at Risk" classes in the testing dataset
Statistics
Predicting using the NaiveBayes classification model
Naive Bayes Predictor
Evaluating the performanceof the model
Scorer (JavaScript)
Evaluating the performanceof the model
Scorer (JavaScript)
Training the Naive Bayesclassification model
Naive Bayes Learner
Evaluating the performanceof the model
Scorer (JavaScript)
Visualizing relationshipbetween "pm10" pollutantand % hospital admissions
Scatter Plot
Visualizing relationshipbetween NO2 concentrationand % hospital admissions
Scatter Plot
Visualizing relationshipbetween "pm2_5" pollutantand % hospital admissions
Scatter Plot
% hospital admissionsby population density
Bar Chart
Visualizing relationshipbetween ozone concentrationand % hospital admissions
Scatter Plot
Visualizing relationshipbetween average daily temperaturesand % hospital admissions
Scatter Plot
Reading in the inputdata provided
CSV Reader
Computing the percentageof hospital admissions
Math Formula
Training the Decision Treeclassification model
Decision Tree Learner
Predicting using the Decision Tree classification model
Decision Tree Predictor
Partitioning the data intotraining and testing datasets
Table Partitioner
Creating expression toindicate seriousness of public health outbreak through the "Risk Status"
Expression
Evaluating the performanceof the model
Scorer
Evaluating the performanceof the model
Scorer
Optimizing the "Min numberrecords per node"
Parameter Optimization Loop Start
Visualizing relationshipbetween AQI and% hospital admissions
Scatter Plot
Overview of % hospitaladmissions by city
Box Plot
Optimizing the "Maximum number of unique nominalvalues per attribute"
Parameter Optimization Loop End
Optimizing the "Maximum number of unique nominalvalues per attribute"
Parameter Optimization Loop Start
Optimizing the "Min numberrecords per node"
Parameter Optimization Loop End
Evaluating the performanceof the model
Scorer
Visualizing the data tosee if any further cleaningor preprocessing is needed
Statistics
Linear Correlation
Scatter Plot
GroupBy
Optimizing the"Number of models"
Parameter Optimization Loop Start
Scatter Plot
Color Manager
Lag Column
Generating the ROC Curve
ROC Curve
Computing the percentageof hospital admissions
Expression
GroupBy
Excluding the "hospital_admissions"and "date" columns fromtraining and testing
Column Filter
Training and predicting usingthe SVM classification model
K Nearest Neighbor
GroupBy
Optimizing the"Number of models"
Parameter Optimization Loop End
Bar Chart
% hospitaladmissions by city
Bar Chart
Color Manager
Table Partitioner
Column Filter
Evaluating the performanceof the model
Scorer (JavaScript)
Bar Chart
Encoding thecategorical variables
One to Many

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: khaledalmuwahed
Created at: 2025-10-01
On NodePit since: 2026-04-19
Last update: 2026-05-09
Created with KNIME version: v5.11.0

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