Business Data Analytics: First International Conference, ICBDA 2022, Dehradun, India, October 7–8, 2022, Proceedings

Description

This book constitutes the proceedings of the First International Conference on Business Data Analytics (ICBDA 2022) held in Dehradun, India, in October 7–8, 2022.  The purpose of conference is to bring the diverse community of data scientist, machine learning, analytics, and data specialist from all over the world to share their original piece research. The 6 full papers included in this proceedings were selected among 107 submissions in a single-blind review process. The theme of conference includes three sub categories: Predictive Modelling and Data Analytics, Decision Analytics and Support System and Business data Analytics. Preface Organization Contents Brain Stroke Prediction Using the Artificial Intelligence 1 Introduction 2 Literature Review 3 Data Set and Methodology Used 4 Data Analysis 5 Results and Discussion 5.1 Model of Ensemble Voting 6 Conclusion References Game Rules Prediction – Winning Strategies Using Decision Tree Algorithms 1 Introduction 2 Literature Review 3 Methodology 4 Analysis and Results 4.1 Exploratory Data Analysis 5 Managerial Applications 6 Methodological Limitations 7 Conclusion References Quantitative Analysis of the Impact of Demography and Job Profile on the Organizational Commitment of the Faculty Members in the HEI’S of Uttarakhand 1 Introduction 2 Literature Review 3 Research Methodology 4 Data Analysis and Interpretation References Prostate Cancer Data Analytics Using Hybrid ECNN and ERNN Techniques 1 Introduction 2 Literature Survey 3 Research Methodology 3.1 Existing System 3.2 Proposed System 4 Experimental Results 4.1 ECNN Algorithm 4.2 ERNN Algorithm 4.3 Input Datset 5 Results 5.1 Performance Evaluation Methods 5.2 Evaluation Metrics 5.3 Data Input 6 Comparison Table 7 Conclusions References A Review on Smart Patient Monitoring and Management in Orthopaedics Using Machine Learning 1 Introduction 2 Problems Related to Bones 2.1 Bone Fracture 2.2 Bone Diseases 2.3 Bone Surgery 3 Role of ML in Orthopaedics 3.1 ML in Fracture Detection 3.2 ML in Fracture Prediction 3.3 ML in the Sphere of Bone Diseases 3.4 ML in Aid of Bone Surgery 4 Conclusions References A Machine Learning Framework for Detection of Fake News 1 Introduction 2 Literature Review 3 Methodology 3.1 Dataset Description 3.2 Feature Extraction Using TF-IDF 3.3 Machine Learning Models 4 Result and Analysis 5 Conclusion References Author Index