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kNN iris

kNN classification model -- iris data1. Data is read from the table file2. Colors are assigned to different classes of iris -- visualization via scatter plots3. Partitioning to the training data (70%) and testing data (30%)4. Normalization to [0,1]5. Training data = model. The prediction is based on kNN classifier6. Model assessment reading thedata tableAssigning colorsfor different irisesTraining 70%Testing 30%Normalizing training datato [0,1]Normalizingtesting datato [0,1]Scatter plotmodel=training dataprediciton based onthe kNN modelModel assessment Table Reader Color Manager Partitioning Normalizer Normalizer (Apply) Scatter Plot K Nearest Neighbor Scorer (JavaScript) kNN classification model -- iris data1. Data is read from the table file2. Colors are assigned to different classes of iris -- visualization via scatter plots3. Partitioning to the training data (70%) and testing data (30%)4. Normalization to [0,1]5. Training data = model. The prediction is based on kNN classifier6. Model assessment reading thedata tableAssigning colorsfor different irisesTraining 70%Testing 30%Normalizing training datato [0,1]Normalizingtesting datato [0,1]Scatter plotmodel=training dataprediciton based onthe kNN modelModel assessmentTable Reader Color Manager Partitioning Normalizer Normalizer (Apply) Scatter Plot K Nearest Neighbor Scorer (JavaScript)

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Created by: Satoru
Created at: 2022-12-06
On NodePit since: 2022-12-06
Last update: 2024-05-01
Created with KNIME version: v4.6.3

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