Using the decision tree technique based on entropy calculation, this application calculates the hit rate of the HASTIE file with a hit rate higher than 99%
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Updated
Dec 23, 2021 - Python
Using the decision tree technique based on entropy calculation, this application calculates the hit rate of the HASTIE file with a hit rate higher than 99%
Using the Sklearn classifiers: Naive Bayes, Random Forest, Adaboost, Gradient Boost, Logistic Regression and Decision Tree good success rates are observed in a very simple manner. In this work sensitivity is also considered. Treating each record individually, differences are found in the results for each record depending on the model used, which…
Taking into account that the accuracy of statistical results depend on the accuracy of the input data, not only on the algorithm, a Hastie file has been created in which all the records have the correct class assigned and tests of hit rates and sensitivity have been carried out
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