Statistics View to show the min, max, mean std etc.
Column Filter to keep only the
Fuel Type
Industry Type
Pie Chart to show the percentage of
Transaction Type
Target Trade Action
Rule Engine to convert
"Buy" to "1"
"Sell" to "0"
Rule Engine to add a column that shows if the Transaction Type meets the Target Trade Action (Yes/No)
Pie Chart to show the percentage of Transaction Types meeting the Target Trade Action
Emission Produced
Emissions Allowance
Math Formula to add a "Carbon Gap" column
Emission Produced-Emission Allowance
Rule Engine to predict
+ Carbon Gap = Buy
- Carbon Gap = Sell
Rule Engine to show if the prediction matches the actual Transaction Type
Pie Chart to show percentage of prediction being correct
Column Filter to remove irrelevant data
Column Filter to remove the
Emission allowed
Convert categorical variables to 1 and 0
Remove old columns
Data Understanding
Model 1 (Carbon Gap)
Normalize the large numerical values
Carbon Gap
Carbon Price
Energy Demand
Sort the columns
Split the data into 80/20
Random Forest Learner using Transaction Type as the target varaible
Random Forest Predictor to predict the Transaction Type for the 20% test data
Scorer used to show the accuracy of the Random Forest Predictor
Modeling
Column Resorter to sort the columns
Column Splitter used to separate the string columns and the numerical columns
Data Preparation
Model 2 (verification status)
Row Filter to keep only the verified transactions
Emission Allowance
Scatter Plot to show the relationships
Improved Model 1 (Remove Normalizer)
Model 3 (Numeric Outlier)
Numeric Outlier to remove rows that contain outliers
Final Model
Row Filter to keep only the rows of companies looking to Buy carbon credits
Column Filter to keep only the Company ID
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
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