/Application-of-Linear-Logistic-Decision-Tree-Random-Forest-Naive-Bayes-in-the-data-sets

It includes the task of loading different data sets and then performing following ML algos in the data sets

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Application-of-Linear-Logistic-Decision-Tree-Random-Forest-Naive-Bayes-in-the-data-sets

It includes the task of loading different data sets and then performing following ML algos in the data sets First of all the data sets are read through importing pandas library with pd.read_csv Then following ML algos are used like 1)Linear Regression 2)Logistic Regression 3)Decision Tree 4)Random Forest 5)Naive Bayes

For this two data sets are used 1)data.csv 2)Diabetes

In this repositories we have used the sklearn library to import Linear,Logistic and other ML models for experiment This is very uselful for ML and other applications too