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General Analysis (Before PreProcessing) General Analysis (AfterProcessing) Convert the zeros on data to nan then handling the missing values with median according to positive and negativeoutcomes Convert numerical columns like glucose and Age...to intervalhelp for visualize data and more.. A flow Variable for dynamic choose and Analysis. Target Analysis Glucose Analysis BloodPressure Analysis Choose Col to Analysis Feature Selection and Model Selection Random Forest Gradient Boosting XGBoost Generate New column using k- means Hyperparameters Optimization and Training a Random Forest Model deployment We Read The Data (Diabetes)General Statistics The Correlation between the columnsDetect outliersValue counter for the prediction colHeatmapCleaning Data And handling missing valuesGeneral Statistics The Correlation between the columnsDetect outliersValue counter for the prediction colHeatmapconvert numerical column to interval Sunburst for OutcomeDist of Glucose(boxplot)Dist of Glucose(barplot)Percentage of Diabetes and not DiabetesNumber of Diabetes and not DiabetesPercentage of GlucoseAnalysis for Glucose in data setOutcome vs Columns(Boxplot)General Analysis for OutcomeOutcome vs Columns(Boxplot)Change in overcome over some featuresStatistical info #1Statistical info #2mean of every feature by Glucose categoryRealtionship between Glucose and Other featuresChanges in some FeaturesOver GlucosePercentage of BloodPressuremean of every feature by BloodPressure categoryRealtionship between BloodPressure and Other featuresChanges in some FeaturesOver BloodPressureAnalysis for BloodPressure in data setDist of BloodPressure(boxplot)Dist of BloodPressure(barplot)mean of every feature by Variable categoryRealtionship between Variable and Other featuresChanges in some FeaturesOver VariableAnalysis for Variable in data setChoose Any Col toAnlysisremove the outcome column from dataGenerate new column asfeature engNode 81Node 82Node 83Node 84Node 96Node 97Cluster Assigner for new dataNode 100Node 109Node 111Node 114Node 115Node 116Node 121Node 125Node 126Node 127Node 128Node 129Node 131Node 134Node 135Node 139Node 140Node 141Node 142Node 143Node 144Node 146Node 147Node 148Node 149Node 150Node 151Node 152Node 154 CSV Reader Statistics Linear Correlation Numeric Outliers Value Counter Heatmap(JavaScript) Python Script Statistics Linear Correlation Numeric Outliers Value Counter Heatmap(JavaScript) Python Script Sunburst Chart Box Plot Histogram Pie Chart Bar Chart Pie Chart Python View Python View Python View Python View Python View Python View Python View Python View Python View Python View Pie Chart Python View Python View Python View Python View Box Plot Histogram Python View Python View Python View Python View Variable Creator Column Splitter k-Means Gradient BoostedTrees Learner Gradient BoostedTrees Predictor Random ForestLearner Random ForestPredictor XGBoost LinearModel Learner XGBoost Predictor Cluster Assigner Scorer Scorer Scorer Partitioning Partitioning Partitioning Feature SelectionLoop Start (1:1) Feature SelectionLoop End Feature SelectionLoop Start (1:1) Feature SelectionLoop Start (1:1) Feature SelectionLoop End Feature SelectionLoop End Feature SelectionFilter Random ForestPredictor Scorer X-Partitioner X-Aggregator Parameter OptimizationLoop Start ParameterOptimization Loop End Random ForestLearner Partitioning Random ForestPredictor Scorer ROC Curve Lift Chart(JavaScript) SMOTE Table RowTo Variable Random ForestLearner Model Writer General Analysis (Before PreProcessing) General Analysis (AfterProcessing) Convert the zeros on data to nan then handling the missing values with median according to positive and negativeoutcomes Convert numerical columns like glucose and Age...to intervalhelp for visualize data and more.. A flow Variable for dynamic choose and Analysis. Target Analysis Glucose Analysis BloodPressure Analysis Choose Col to Analysis Feature Selection and Model Selection Random Forest Gradient Boosting XGBoost Generate New column using k- means Hyperparameters Optimization and Training a Random Forest Model deployment We Read The Data (Diabetes)General Statistics The Correlation between the columnsDetect outliersValue counter for the prediction colHeatmapCleaning Data And handling missing valuesGeneral Statistics The Correlation between the columnsDetect outliersValue counter for the prediction colHeatmapconvert numerical column to interval Sunburst for OutcomeDist of Glucose(boxplot)Dist of Glucose(barplot)Percentage of Diabetes and not DiabetesNumber of Diabetes and not DiabetesPercentage of GlucoseAnalysis for Glucose in data setOutcome vs Columns(Boxplot)General Analysis for OutcomeOutcome vs Columns(Boxplot)Change in overcome over some featuresStatistical info #1Statistical info #2mean of every feature by Glucose categoryRealtionship between Glucose and Other featuresChanges in some FeaturesOver GlucosePercentage of BloodPressuremean of every feature by BloodPressure categoryRealtionship between BloodPressure and Other featuresChanges in some FeaturesOver BloodPressureAnalysis for BloodPressure in data setDist of BloodPressure(boxplot)Dist of BloodPressure(barplot)mean of every feature by Variable categoryRealtionship between Variable and Other featuresChanges in some FeaturesOver VariableAnalysis for Variable in data setChoose Any Col toAnlysisremove the outcome column from dataGenerate new column asfeature engNode 81Node 82Node 83Node 84Node 96Node 97Cluster Assigner for new dataNode 100Node 109Node 111Node 114Node 115Node 116Node 121Node 125Node 126Node 127Node 128Node 129Node 131Node 134Node 135Node 139Node 140Node 141Node 142Node 143Node 144Node 146Node 147Node 148Node 149Node 150Node 151Node 152Node 154 CSV Reader Statistics Linear Correlation Numeric Outliers Value Counter Heatmap(JavaScript) Python Script Statistics Linear Correlation Numeric Outliers Value Counter Heatmap(JavaScript) Python Script Sunburst Chart Box Plot Histogram Pie Chart Bar Chart Pie Chart Python View Python View Python View Python View Python View Python View Python View Python View Python View Python View Pie Chart Python View Python View Python View Python View Box Plot Histogram Python View Python View Python View Python View Variable Creator Column Splitter k-Means Gradient BoostedTrees Learner Gradient BoostedTrees Predictor Random ForestLearner Random ForestPredictor XGBoost LinearModel Learner XGBoost Predictor Cluster Assigner Scorer Scorer Scorer Partitioning Partitioning Partitioning Feature SelectionLoop Start (1:1) Feature SelectionLoop End Feature SelectionLoop Start (1:1) Feature SelectionLoop Start (1:1) Feature SelectionLoop End Feature SelectionLoop End Feature SelectionFilter Random ForestPredictor Scorer X-Partitioner X-Aggregator Parameter OptimizationLoop Start ParameterOptimization Loop End Random ForestLearner Partitioning Random ForestPredictor Scorer ROC Curve Lift Chart(JavaScript) SMOTE Table RowTo Variable Random ForestLearner Model Writer

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Created by: WeWillNotForget_H
Created at: 2023-12-30
On NodePit since: 2024-01-04
Last update: 2024-04-27
Created with KNIME version: v5.1.2

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