Quantum Modelling - IBM HR Attrition Dataset

Description

This is the dataset developed using data Pavansubhash. (2017). IBM HR Analytics Employee Attrition & Performance. https://www.kaggle.com/datasets/pavansubhasht/ibm-hr-analytics-attrition-dataset/data The data has been preprocessed as clean, noisy and imbalanced and machine learning has been attempted to apply and test classical models such as RandomForest, SVM, LogisticRegression, GradientBoosting, NNN, NaiveBayes, DecisionTree, and also Quantum Models such as QuantumKernel, QSVC, VQC_shallow, VQC_deep. The models were compared using metrics such as Accuracy, Precision, Recall, F1, Time and a Confusion Matrix was developed. The code used for preprocessing, classical and quantum modelling has been provided, Software and environment the code was operated details has been added The Clean, Noisy and Imbalanced datasets were provided Final Results were also added

Steps to reproduce

The steps have been given in the code and also the description

Institutions

• Aditya University

  Andhra Pradesh, Sūrampālem

Categories

Licence