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Predict sales for a retail store with linear regression

- Prepare train and test data
- Treat missing value
- Finding correlation
- Train a Linear Regression model
- Apply trained regression model to the test data
- Write prediction to a CSV file


Data Vizualisationsfinding what item is sold the maximum out ofthe others Test data preparation Problem statement:The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores indifferent cities. Also, certain attributes of each product and store have been defined. The aim is tobuild a predictive model and find out the sales of each product at a particular store.Scope:Using this model, BigMart will try to understand the properties of products and stores which play akey role in increasing sales. Intractive tabledisplay table of the entire data Training data preparation Train model Selecting columns and writing data to csv file Apply the model File reader for train dataCorrelationScatter plotPie chartTreating missing valueLinear regression trainingfile reader for test dataTreating missing valueregression predictorfilter required columnwrite output in csv fileshow entire data as tableFile Reader Linear Correlation Scatter Plot Pie/Donut Chart Missing Value Linear RegressionLearner File Reader Missing Value RegressionPredictor Column Filter CSV Writer InteractiveTable (local) Data Vizualisationsfinding what item is sold the maximum out ofthe others Test data preparation Problem statement:The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores indifferent cities. Also, certain attributes of each product and store have been defined. The aim is tobuild a predictive model and find out the sales of each product at a particular store.Scope:Using this model, BigMart will try to understand the properties of products and stores which play akey role in increasing sales. Intractive tabledisplay table of the entire data Training data preparation Train model Selecting columns and writing data to csv file Apply the model File reader for train dataCorrelationScatter plotPie chartTreating missing valueLinear regression trainingfile reader for test dataTreating missing valueregression predictorfilter required columnwrite output in csv fileshow entire data as tableFile Reader Linear Correlation Scatter Plot Pie/Donut Chart Missing Value Linear RegressionLearner File Reader Missing Value RegressionPredictor Column Filter CSV Writer InteractiveTable (local)

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Created by: knoldus
Created at: 2020-05-14
On NodePit since: 2020-05-23
Last update: 2024-11-21
Created with KNIME version: v4.1.2
Tags: Linear Regressionmachine learninganalysisread-writePredictioninputoutputsalesRetail

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