Research on Bayesian statistical application to analyze the willingness to participate in coffee crop insurance based on productivity index of farming households in Dak Lak province - 28


Appendix 7.15: Confusion matrix and prediction results of BMAL1 model when using the entire data


Source: Author's calculation results

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Appendix 7.16: Bootstrap results of model BMAL1


Source: Author's calculation results


Appendix 7.17: Confusion matrix and prediction results of BMAL2 model when using the entire data


Source: Author's calculation results

Appendix 7.18: Bootstrap results of the BMAL2 model


Source: Author's calculation results


Appendix 7.19: Confusion matrix and prediction results of BMAL3 model when using the entire data



Source: Author's calculation results


Appendix 7.20: Bootstrap results of the BMAL3 model


Source: Author's calculation results


Appendix 7.21: Confusion matrix and prediction results of BMAL4 model when using the entire data



Source: Author's calculation results


Appendix 7.22: Bootstrap results of the BMAL4 model


Source: Author's calculation results


Appendix 7.23: Confusion matrix and prediction results of BMAL5 model when using the entire data



Source: Author's calculation results


Appendix 7.24: Bootstrap results of the BMAL5 model


Source: Author's calculation results


Appendix 7.25: Confusion matrix and prediction results of BMAL6 model when using the entire data



Source: Author's calculation results


Appendix 7.26: Bootstrap results of the BMAL6 model


Source: Author's calculation results


Appendix 7.27: Confusion matrix and prediction results of BMAL1_Split model when using training data


Source: Author's calculation results

Appendix 7.28: Bootstrap results of the BMAL1_Split model


Source: Author's calculation results


Appendix 7.29: Confusion matrix and prediction results of BMAL2_Split model when using training data


Source: Author's calculation results

Appendix 7.30: Bootstrap results of the BMAL2_Split model


Source: Author's calculation results

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