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Yield Forecast

Final Project: Yield Forecasting for LA Rice MillDescription: The data set makes use of historical rice yield and seed type from the Philippine Statistics Authority (PSA) in Oriental Mindoro and Daily Temperature and Precipity values taken frommeteoblue. The dataset used ranged from 2014 until 2019. The prediction task aims to forecast the rice yield for LA Rice Mill using the daily temperature, seed type, dailyprecipitation, and quarterly harvests made in Oriental Mindoro. The models used for the prediction task are Multiple Linear Regression and Regression Tree. Merge DataParse DateParse QuarterParse YearConvert Year to StringTop: Training Set (70%)Bottom: Test Set (30%)Take From Top (Sorted by Date)Train the Model to Forecast Rice YieldApply the Model to the Test SetEvaluate Model PerformanceNormalize Missing ValuesDaily Temperature RecordsRice Yield RecordsConvert Year to StringMerge DataTop: Training Set (70%)Bottom: Test Set (30%)Take From Top (Sorted by Date)Evaluate Model PerformanceParse YearParse QuarterParse DateNormalize Missing ValuesTrain the Model to Forecast Rice YieldApply the Model to the Test SetDaily TemperatureRice Yield Records Joiner String Manipulation Rule Engine String Replacer Number To String Partitioning Linear RegressionLearner RegressionPredictor Numeric Scorer Missing Value CSV Reader CSV Reader Number To String Joiner Partitioning Numeric Scorer String Replacer Rule Engine String Manipulation Missing Value Simple RegressionTree Learner Simple RegressionTree Predictor CSV Reader CSV Reader Final Project: Yield Forecasting for LA Rice MillDescription: The data set makes use of historical rice yield and seed type from the Philippine Statistics Authority (PSA) in Oriental Mindoro and Daily Temperature and Precipity values taken frommeteoblue. The dataset used ranged from 2014 until 2019. The prediction task aims to forecast the rice yield for LA Rice Mill using the daily temperature, seed type, dailyprecipitation, and quarterly harvests made in Oriental Mindoro. The models used for the prediction task are Multiple Linear Regression and Regression Tree. Merge DataParse DateParse QuarterParse YearConvert Year to StringTop: Training Set (70%)Bottom: Test Set (30%)Take From Top (Sorted by Date)Train the Model to Forecast Rice YieldApply the Model to the Test SetEvaluate Model PerformanceNormalize Missing ValuesDaily Temperature RecordsRice Yield RecordsConvert Year to StringMerge DataTop: Training Set (70%)Bottom: Test Set (30%)Take From Top (Sorted by Date)Evaluate Model PerformanceParse YearParse QuarterParse DateNormalize Missing ValuesTrain the Model to Forecast Rice YieldApply the Model to the Test SetDaily TemperatureRice Yield RecordsJoiner String Manipulation Rule Engine String Replacer Number To String Partitioning Linear RegressionLearner RegressionPredictor Numeric Scorer Missing Value CSV Reader CSV Reader Number To String Joiner Partitioning Numeric Scorer String Replacer Rule Engine String Manipulation Missing Value Simple RegressionTree Learner Simple RegressionTree Predictor CSV Reader CSV Reader

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Created by: martin
Created at: 2021-09-15
On NodePit since: 2021-09-16
Last update: 2024-11-21
Created with KNIME version: v4.4.0

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