company provided historical claim data for the data mining model.The available dataset has 150000 records

company provided historical data for the 150.000 records. After data cleaning the data de training and test sots. The training data has 120.000 seconds and legitimate claims and 10,000 default claims in this training. The used to build the predictive model. The test data has 30.000 records and legitimate claims and 3.000 default claims. The following results are and test data sets In the training data, the data mining model predicted 112.000 claims and 109,000 out of 112,000 actually correspond to the hence, predicted correctly. The remaining 3.000 records were The data mining model predicted 8,000 records as default 8,000 actually correspond to the default claims and hoped remaining 1000 records were actually legitimate chains The data mining model predicted 3.200 records as default claims and 1200 out of 3,200 actually correspond to the default claims and hence, predicand comectly. The remaining 2000 records were actually legitimate claims. Calculate the confusion matrices for both training and tested results show you on and calculations. Interpret the content of the confusion matrix for both training and tas set results. Interpret Type I and Type Il errors considering this data mining problem Which error type is more important for this problem? Explain your asning company provided historical data for the 150.000 records. After data cleaning the data de training and test sots. The training data has 120.000 seconds and legitimate claims and 10,000 default claims in this training. The used to build the predictive model. The test data has 30.000 records and legitimate claims and 3.000 default claims. The following results are and test data sets In the training data, the data mining model predicted 112.000 claims and 109,000 out of 112,000 actually correspond to the hence, predicted correctly. The remaining 3.000 records were The data mining model predicted 8,000 records as default 8,000 actually correspond to the default claims and hoped remaining 1000 records were actually legitimate chains The data mining model predicted 3.200 records as default claims and 1200 out of 3,200 actually correspond to the default claims and hence, predicand comectly. The remaining 2000 records were actually legitimate claims. Calculate the confusion matrices for both training and tested results show you on and calculations. Interpret the content of the confusion matrix for both training and tas set results. Interpret Type I and Type Il errors considering this data mining problem Which error type is more important for this problem? Explain your asning