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Sharing_​Components_​with_​Bundled_​Python_​packages

Sharing Component with Bundled Python Packages (kNN Regression)

This workflow demonstrates the process of Scripted Component creation. In this example, a Component is created for kNN Regression using the scikit-kearn python package. The scikit-learn package is available in the bunled environment that comes with the the Python Script node, which is why this node uses the bundled environment for execution.

Read and Manipulate Data Train the kNN Regressor usingPython Package Scikit-Learn Workflow Inside of Component kNN Regression (Displayed here for KNIME Hub Inspection) Adopting Python Bundled Packages : Download and open this workflow to auto-install requirements and execute the Python scripts. This workflow uses a node from KNIMEPython Integration, which installs Python and a number of pre-defined packages on your system. Supported on KNIME Analytics Platform4.7 or higher. Confiuration Dialog Calculate Model Performance and Visualize Train kNN regressorOutput Port 0: Regression OutputPort 1: Regression ModelRead BostonHousing DataChange datatype of columnsVsiualizeActual vs Predicted valuesSelect 50 rows to visualizeAssign ColorsUser Input for value of kWrite Model Performancein a fileTrain Regression modelto predict House PricesShow the user inputCalculate Performance StatsShow Performance StatsComponent InputPython Script CSV Reader Table Manipulator Line Plot Row Sampling Extract Table Spec Color Manager IntegerConfiguration CSV Writer kNN Regression Text Output Widget Numeric Scorer Table View Table Creator Read and Manipulate Data Train the kNN Regressor usingPython Package Scikit-Learn Workflow Inside of Component kNN Regression (Displayed here for KNIME Hub Inspection) Adopting Python Bundled Packages : Download and open this workflow to auto-install requirements and execute the Python scripts. This workflow uses a node from KNIMEPython Integration, which installs Python and a number of pre-defined packages on your system. Supported on KNIME Analytics Platform4.7 or higher. Confiuration Dialog Calculate Model Performance and Visualize Train kNN regressorOutput Port 0: Regression OutputPort 1: Regression ModelRead BostonHousing DataChange datatype of columnsVsiualizeActual vs Predicted valuesSelect 50 rows to visualizeAssign ColorsUser Input for value of kWrite Model Performancein a fileTrain Regression modelto predict House PricesShow the user inputCalculate Performance StatsShow Performance StatsComponent InputPython Script CSV Reader Table Manipulator Line Plot Row Sampling Extract Table Spec Color Manager IntegerConfiguration CSV Writer kNN Regression Text Output Widget Numeric Scorer Table View Table Creator

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