- The first model is a Linear Regression model which is used to predict the scores of a student given the number of hours he/she studies.
The data contains a single feature which is the number of hours studied by a student. As the data is simple and contains only one feature, Linear Regression is the optimal algorithm and upon completion it was found that the model obtained an accuracy of 96%. - The second model is a Decision Tree model which predicts whether the user is eligible for the loan or not.
- The third model is the classification of iris dataet with the Naive Bayes algorithm.
suhasml/ML-projects-1
Linear Regression model to predict student's percentage.
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