This is my first classification project where we need to classify whether the person will get loan or not according to the different parameters. The training dataset contains 614 observations and 13 independent variables and we have an incomplete dataset.

Libraries Used: numpy,pandas,matplot, sklearn

Data visualization is used to fill the missing values.

Cross validation is also used for proper training of the dataset and different machine learning algorithms are used to train the dataset.

Accuracies Found On the training dataset:

Logistic Regression : 82.40%

Random Forest : 76.97%

Decision Tree: 70.66%

Logistic Regression has given maximum accuracy as the relationship is linear between independent and dependent variable.