This is a Premiere Project done by Team Gitlab in Hamoye Data Science Program Dec'22. Out of 5 models used on the data, Random Forest Classifier was used to further improve the prediction of characters death. With parameter tuning and few cross validation, we were able to reduce the base error by 5.42% and increase accuracy by 2,42%.
machine-learning
prediction
classification
teamwork
parameter-tuning
random-forest-classifier
gridsearchcv
modelselection
crossvalidation
randomsearch-cv
hamoye
hamoyedatascienceinternship
premiere-project
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Updated
Sep 1, 2023 - Jupyter Notebook