The workflow trains a Linear Regression model to predict the price of a Lego set based on it's various features. It includes the process of: - Loading the Lego dataset and cleaning it to remove missing values and outliers - Remove collinearity between independent variables - Partitioning the dataset into train and test dataset - Modelling a Linear Regressor and prediciting sales of lego sets in test data - Calculate the accuracy metrics of the model - Plot residual plot and histogram to visualize Linear Regression assumptions of homoscedasticity (constant variance) and normal distribution of error.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.1.3
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