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SVC and KNN methods were used to predict whether mushrooms are poisonous or edible according to their properties. Random forest and chi-square variable selection methods were applied and the 10-fold cross validation method was used and f1 scores were calculated by re-estimating. Finally, the models were compared.

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mushrooms.csv		mushrooms.csv

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MantarSiniflandirma

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SVC and KNN methods were used to predict whether mushrooms are poisonous or edible according to their properties. Random forest and chi-square variable selection methods were applied and the 10-fold cross validation method was used and f1 scores were calculated by re-estimating. Finally, the models were compared.

data-science cross-validation variable-importance eda data-visualization variable-selection data-analysis multiclass-classification f1-score knn-classification model-compression svc-model

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