/Medical-Appointment-Presence-Prediction

To analyze whether the patients who made the appointment will show up or not. • Data acquisition and cleaning • EDA – bar graphs, box plot, pie-chart • Data manipulation and treating categorical features • Train-Test Split • Models tested – KNN, Gaussian Naïve Bayes, Decision Tree Classifier, Random Forest, Gradient Boosting Classifier • Comparing models using performance metrics such as Area under ROC, Accuracy, Precision, Recall and Specificity • Software/Tools/Programming Language Used: Python, NumPy, Pandas, Matplotlib, Plotly

Primary LanguageJupyter Notebook

Medical-Appointment-Presence-Prediction

To analyze whether the patients who made the appointment will show up or not.

• Data acquisition and cleaning

• EDA – bar graphs, box plot, pie-chart

• Data manipulation and treating categorical features

• Train-Test Split

• Models tested – KNN, Gaussian Naïve Bayes, Decision Tree Classifier, Random Forest, Gradient Boosting Classifier

• Comparing models using performance metrics such as Area under ROC, Accuracy, Precision, Recall and Specificity

• Software/Tools/Programming Language Used: Python, NumPy, Pandas, Matplotlib, Plotly