Machine Learning to predict diabetes
The objective of the dataset is to diagnostically predict if a patient has diabetes, established on definite diagnostic quantities incorporated in the dataset.
Content The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.
Dependencies include python libraries like
sklearn
matplotlib
pandas
seaborn
Classification models used
Decision Trees
Ramdom forest
Logistic Regression
SVM
Niave bayes
Logistic Regression
Ensemble Modeling
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Data source: Kaggle
